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.     

Perisynaptic Schwann Cells at the Neuromuscular Synapse: Adaptable,Multitasking Glial Cells

The neuromuscular junction (NMJ) is engineered to be a highly reliable synapse to carry the control of the motor commands of the nervous system over the muscles. Its development, organization, and synaptic properties are highly structured and regulated to support such reliability and efficacy. Yet, the NMJ is also highly plastic, able to react to injury and adapt to changes. This balance between structural stability and synaptic efficacy on one hand and structural plasticity and repair on another hand is made possible by the intricate regulation of perisynaptic Schwann cells, glial cells at this synapse. They regulate both the efficacy and structural plasticity of the NMJ in a dynamic, bidirectional manner owing to their ability to decode synaptic transmission and by their interactions via trophic-related factors.The vertebrate neuromuscular junction (NMJ), arguably the best characterized synapse in the peripheral nervous system (PNS), is composed of three closely associated cellular components: the presynaptic nerve terminal, the postsynaptic specialization, and nonmyelinating Schwann cells. These synapse-associated glial cells are called perisynaptic Schwann cells (PSCs), or terminal Schwann cells (see reviews by Todd and Robitaille 2006; Feng and Ko 2007; Griffin and Thompson 2008; Sugiura and Lin 2011). Multiple roles of PSCs have gained great appreciation since the 1990s and, along with the novel roles of astrocytes in central synapses, have led to the concept of the “tripartite” synapse (Araque et al. 1999, 2014; Volterra et al. 2002; Auld and Robitaille 2003; Kettenmann and Ransom 2013).Thus, to fully understand synaptic formation and function, it is critical to also consider the active and essential roles of synapse-associated glial cells. We will discuss evidence supporting the existence of a synapse–glia–synapse regulatory loop that helps maintain and restore synaptic efficacy at the NMJ. We will also explore the multiple functions that PSCs exert, functions that are adapted to a given situation at the NMJ (e.g., synapse formation, stability, and reinnervation). This will highlight the great adaptability and plasticity of the morphological and functional properties of PSCs.In this review, we will focus on the multiple roles PSCs play in synaptic formation, maintenance, remodeling, and regeneration, as well as synaptic function and plasticity. Based on the evidence presented, we propose a model in which PSCs, through specific receptor activation, play a prominent role in a continuum of synaptic efficacy, stability, and plasticity at the NMJ. These synaptic-regulated functions allow PSCs to orchestrate the stability and plasticity of the NMJ and, hence, are important for maintaining and adapting synaptic efficacy.     

Presynaptic Membrane Retrieval and Endosome Biology: Defining Molecularly Heterogeneous Synaptic Vesicles

The release and uptake of neurotransmitters by synaptic vesicles is a tightly controlled process that occurs in response to diverse stimuli at morphologically disparate synapses. To meet these architectural and functional synaptic demands, it follows that there should be diversity in the mechanisms that control their secretion and retrieval and possibly in the composition of synaptic vesicles within the same terminal. Here we pay particular attention to areas where such diversity is generated, such as the variance in exocytosis/endocytosis coupling, SNAREs defining functionally diverse synaptic vesicle populations and the adaptor-dependent sorting machineries capable of generating vesicle diversity. We argue that there are various synaptic vesicle recycling pathways at any given synapse and discuss several lines of evidence that support the role of the endosome in synaptic vesicle recycling.Chemical synapses contain discrete numbers of synaptic vesicles, which are capable of sustaining neurotransmitter release. Sustained neurotransmission occurs despite the secretory demands imposed by persistent and diverse patterns of neuronal electrical activity. Maintaining synaptic vesicle numbers requires local mechanisms to regenerate these vesicles to prevent their exhaustion, preserve plasma membrane surface area, and to maintain the molecularly distinct identity of a vesicle versus plasma membrane. Rizzoli and Betz (2005) eloquently draw a parallel between chemical neurotransmission with synapse chatter saying that some synapses “whisper,” whereas others “shout.” The “louder” the synapse, the more synaptic vesicles are required, extending from a few hundred vesicles (whisperers) to nearly thousands (shouters). This beautiful analogy implies that every synapse has just one “voice” or species of vesicle. Here we will present the case that synapses are more like choirs in which multiple vesicle species or “voices” contribute to the “pianissimo” or “fortissimo” parts of chemical neurotransmission.Synaptic terminals show a range of structural and functional differences in distinct regions of the brain, suggesting that the mechanisms for exocytosis/endocytosis coupling, as well as local vesicle recycling, may also be diverse. On one side, the Calyx of Held nerve terminal participates in fast and sustained synaptic transmission at high frequency (800 Hz), which is crucial for sound localization in the auditory brainstem (Taschenberger and von Gersdorff 2000; Borst and Soria van Hoeve 2012). The Calyx of Held houses ∼70,000 synaptic vesicles with nearly 3000 vesicles docked per Calyx terminal. These docked vesicles are distributed across the ∼500 active zones that exist per Calyx where vesicle fusion occurs (Satzler et al. 2002). On the other hand, hippocampal synapses fire action potentials at ∼0.5 Hz in bursts (Dobrunz and Stevens 1999). This synapse contains ∼200 synaptic vesicles and one active zone with ∼10 vesicles docked (Schikorski and Stevens 1997). With such a wide functional and structural gamut of synapses, it is reasonable to hypothesize that synaptic vesicles may differ in their retrieval mechanisms, not just at the rate at which the process occurs but also in the molecular pathways used.Two synaptic vesicle retrieval mechanisms, namely clathrin/AP-2/dynamin-dependent biogenesis and kiss-and-run, have been summarized in outstanding recent reviews (see, for example, Augustine et al. 2006; Rizzoli and Jahn 2007; Smith et al. 2008; Royle and Lagnado 2010; Ferguson and De Camilli 2012; Saheki and De Camilli 2012). Therefore, here we focus on the coupling of secretion and membrane retrieval, as well as endosome sorting. We will discuss new developments supporting the existence of diverse functional and molecular pools of synaptic vesicles and how endocytosis and endosome retrieval mechanisms may generate these vesicle pools.     

Cell Adhesion, the Backbone of the Synapse: ��Vertebrate�� and ��Invertebrate�� Perspectives

Synapses are asymmetric intercellular junctions that mediate neuronal communication. The number, type, and connectivity patterns of synapses determine the formation, maintenance, and function of neural circuitries. The complexity and specificity of synaptogenesis relies upon modulation of adhesive properties, which regulate contact initiation, synapse formation, maturation, and functional plasticity. Disruption of adhesion may result in structural and functional imbalance that may lead to neurodevelopmental diseases, such as autism, or neurodegeneration, such as Alzheimer''s disease. Therefore, understanding the roles of different adhesion protein families in synapse formation is crucial for unraveling the biology of neuronal circuit formation, as well as the pathogenesis of some brain disorders. The present review summarizes some of the knowledge that has been acquired in vertebrate and invertebrate genetic model organisms.Synapses are asymmetric, intercellular junctions that are the basic structural units of neuronal transmission. The correct development of synaptic specializations and the establishment of appropriate connectivity patterns are crucial for the assembly of functional neuronal circuits. Improper synapse formation and function may cause neurodevelopmental disorders, such as mental retardation (MsR) and autism spectrum disorders (ASD) (McAllister 2007; Sudhof 2008), and likely play a role in neurodegenerative disorders, such as Alzheimer''s disease (AD) (Haass and Selkoe 2007).At chemical synapses (reviewed in Sudhof 2004; Zhai and Bellen 2004; Waites et al. 2005; McAllister 2007; Jin and Garner 2008), the presynaptic compartment contains synaptic vesicles (SV), organized in functionally distinct subcellular pools. A subset of SVs docks to the presynaptic membrane around protein-dense release sites, named active zones (AZ). Upon the arrival of an action potential at the terminal, the docked and “primed” SVs fuse with the plasma membrane and release neurotransmitter molecules into the synaptic cleft. Depending on the type of synapse (i.e., excitatory vs. inhibitory synapses), neurotransmitters ultimately activate an appropriate set of postsynaptic receptors that are accurately apposed to the AZ.Synapse formation occurs in several steps (Fig. 1) (reviewed in Eaton and Davis 2003; Goda and Davis 2003; Waites et al. 2005; Garner et al. 2006; Gerrow and El-Husseini 2006; McAllister 2007). Spatiotemporal signals guide axons through heterogeneous cellular environments to contact appropriate postsynaptic targets. At their destination, axonal growth cones initiate synaptogenesis through adhesive interactions with target cells. In the mammalian central nervous system (CNS), immature postsynaptic dendritic spines initially protrude as thin, actin-rich filopodia on the surface of dendrites. Similarly, at the Drosophila neuromuscular junction (NMJ), myopodia develop from the muscles (Ritzenthaler et al. 2000). The stabilization of intercellular contacts and their elaboration into mature, functional synapses involves cytoskeletal arrangements and recruitment of pre- and postsynaptic components to contact sites in spines and boutons. Conversely, retraction of contacts results in synaptic elimination. Both stabilization and retraction sculpt a functional neuronal circuitry.Open in a separate windowFigure 1.(A–C) Different stages of synapse formation. (A) Target selection, (B) Synapse assembly, (C) Synapse maturation and stabilization. (D–F) The role of cell adhesion molecules in synapse formation is exemplified by the paradigm of N-cadherin and catenins in regulation of the morphology and strength of dendritic spine heads. (D) At an early stage the dendritic spines are elongated from motile structures “seeking” their synaptic partners. (E) The contacts between the presynaptic and postsynaptic compartments are stabilized by recruitment of additional cell adhesion molecules. Adhesional interactions activate downstream pathways that remodel the cytoskeleton and organize pre- and postsynaptic apparatuses. (F) Cell adhesion complexes, stabilized by increased synaptic activity, promote the expansion of the dendritic spine head and the maturation/ stabilization of the synapse. Retraction and expansion is dependent on synaptic plasticity.In addition to the plastic nature of synapse formation, the vast heterogeneity of synapses (in terms of target selection, morphology, and type of neurotransmitter released) greatly enhances the complexity of synaptogenesis (reviewed in Craig and Boudin 2001; Craig et al. 2006; Gerrow and El-Husseini 2006). The complexity and specificity of synaptogenesis relies upon the modulation of adhesion between the pre- and postsynaptic components (reviewed in Craig et al. 2006; Gerrow and El-Husseini 2006; Piechotta et al. 2006; Dalva et al. 2007; Shapiro et al. 2007; Yamada and Nelson 2007; Gottmann 2008). Cell adhesive interactions enable cell–cell recognition via extracellular domains and also mediate intracellular signaling cascades that affect synapse morphology and organize scaffolding complexes. Thus, cell adhesion molecules (CAMs) coordinate multiple synaptogenic steps.However, in vitro and in vivo studies of vertebrate CAMs are often at odds with each other. Indeed, there are no examples of mutants for synaptic CAMs that exhibit prominent defects in synapse formation. This apparent “resilience” of synapses is probably caused by functional redundancy or compensatory effects among different CAMs (Piechotta et al. 2006). Hence, studies using simpler organisms less riddled by redundancy, such as Caenorhabditis elegans and Drosophila, have aided in our understanding of the role that these molecules play in organizing synapses.In this survey, we discuss the roles of the best characterized CAM families of proteins involved in synaptogenesis. Our focus is to highlight the complex principles that govern the molecular basis of synapse formation and function from a comparative perspective. We will present results from cell culture studies as well as in vivo analyses in vertebrate systems and refer to invertebrate studies, mainly performed in Drosophila and C. elegans, when they have provided important insights into the role of particular CAM protein families. However, we do not discuss secreted factors, for which we refer the reader to numerous excellent reviews (as for example Washbourne et al. 2004; Salinas 2005; Piechotta et al. 2006; Shapiro et al. 2006; Dalva 2007; Yamada and Nelson 2007; Biederer and Stagi 2008; Salinas and Zou 2008).     

Understanding the Structure and Function of the Immunological Synapse

The immunological synapse has been an area of very active scientific interest over the last decade. Surprisingly, much about the synapse remains unknown or is controversial.  Here we review some of these current issues in the field:  how the synapse is defined, its potential role in T-cell function, and our current understanding about how the synapse is formed.T cells are activated when they recognize peptide-MHC complexes on the surface of antigen presenting cells (APC) (Babbitt et al. 1985). But the exact process regarding how antigenic pMHC complexes are recognized and transduced into signals is still incompletely understood. Naïve T cells enter secondary lymphoid organs such as the lymph node and scan dendritic cells for the presence of rare specific pMHC complexes (Miller et al. 2004). After recognizing less than 10 specific pMHC complexes, naïve T cells maintain long contacts (6–18 h) with dendritic cells before being committed to enter cell cycle and differentiate into effector T cells (Iezzi et al. 1998; Irvine et al. 2002; Mempel et al. 2004).The immunological synapse (IS) refers to the organization of membrane proteins that occurs at the interface between the T cell and the APC during these long contacts and also during the effector phase (Grakoui et al. 1999; Monks et al. 1998). Interest in studying the IS stems from ideas that the supramolecular structures that form at the IS underlies the high sensitivity of T cell recognition and that understanding these structures will lead to better insights into how antigen recognition leads to the decision of a T cell to proliferate, differentiate, and function.Springer first put forward the concept that receptors would segregate laterally during cell interactions (Springer 1990). Subsequently, Kupfer was the first to show that proteins in the contact area between a T cell and APC segregate laterally (Monks et al. 1998). Specifically, he noted that the integrin, LFA-1, became concentrated in an outer ring, known as the peripheral supramolecular activation complex (pSMAC) and the TCR became concentrated in the center, in a zone known as the central supramolecular activation complex (cSMAC) (Monks et al. 1998)(Fig. 1). We showed that CD2 could segregate from LFA-1 and concentrate in the center of a hybrid cell-planar bilayer junction and suggested that these patterns and those described by Monks et al. (1998) provided evidence for the previously hypothesized immunological synapse (Dustin et al. 1998; Norcross 1984). The function of this receptor segregation is still not completely understood but it was initially hypothesized that formation of this pattern might be related to T-cell activation and constitute a “molecular machine” that would be formed in response to the presence of antigenic ligand and that this “molecular machine” might function to sustain signaling for long periods of time and direct subsequent T-cell differentiation (Grakoui et al. 1999).Open in a separate windowFigure 1.Structure of the immunological synapse. The basic structure of the “organized” immunological synapse with SMACs is shown (left). In the center is the central supramolecular activation complex or cSMAC, which contains receptors like the TCR, CD28, CD4, CD8, and CD2. Newer studies suggest that the cSMAC may be divided into an outer area containing CD28 and an inner area containing the TCR (not shown). The ring that surrounds the cSMAC is called the peripheral supramolecular activation complex or pSMAC. This domain is mainly populated by the integrin molecule LFA-1. Outside of the pSMAC is another domain known as the distal supramolecular activation complex. Originally the dSMAC was thought not be important and contain all of the molecules that are not specifically recruited to the cSMAC or pSMAC but it is increasingly becoming appreciated that the dSMAC is an area of active membrane movement. This suggests that the pSMAC and dSMAC may be analogous to the actin structures known as the lamellae and lamellipodia, respectively (right).     

Studying Signal Transduction in Single Dendritic Spines

Many forms of synaptic plasticity are triggered by biochemical signaling that occurs in small postsynaptic compartments called dendritic spines, each of which typically houses the postsynaptic terminal associated with a single glutamatergic synapse. Recent advances in optical techniques allow investigators to monitor biochemical signaling in single dendritic spines and thus reveal the signaling mechanisms that link synaptic activity and the induction of synaptic plasticity. This is mostly in the study of Ca²⁺-dependent forms of synaptic plasticity for which many of the steps between Ca²⁺ influx and changes to the synapse are now known. This article introduces the new techniques used to investigate signaling in single dendritic spines and the neurobiological insights that they have produced.Each neuron typically receives 1000–10,000 synaptic inputs and sends information to an axon, which branches to produce a similar number of synaptic outputs. Most excitatory postsynaptic terminals are associated with dendritic spines, small protrusions emanating from the dendritic surface (Nimchinsky et al. 2002; Alvarez and Sabatini 2007). Each spine has a volume of ∼0.1 femtoliter, and connects to the parent dendrite through a narrow neck, which acts as a diffusion barrier and compartmentalizes biochemical reactions. Ca²⁺ influx into spines initiates a cascade of biochemical signals leading to various forms of synaptic plasticity including long-term potentiation (LTP).Because LTP in hippocampal CA1 pyramidal neurons is a cellular mechanism that may underlie long-term memory formation, the signal transduction underlying LTP has been extensively studied by pharmacological and genetic methods (Bliss and Collingridge 1993; Derkach et al. 2007). It is now well established that LTP is induced by Ca²⁺ influx into dendritic spines through NMDA-type glutamate receptors (NMDARs), which induces the insertion of AMPA-type glutamate receptors (AMPARs) into the synapse, thereby increasing the sensitivity of the postsynaptic terminal to glutamate (Derkach et al. 2007; Kessels and Malinow 2009). An increase of release probability during LTP has also been reported (Enoki et al. 2009), and thus both pre- and postsynaptic mechanisms may contribute to LTP (Lisman and Raghavachari 2006).Manipulations of signal transduction using specific pharmacological inhibitors or genetic perturbations have identified many signaling pathways that connect Ca²⁺ to LTP induction. For example, LTP requires the activation of many signaling proteins, including Ca²⁺/calmodulin-dependent kinase II (CaMKII), extracellular signal-related kinase (ERK), Phoshoinositide 3 kinase (PI3K), protein kinase A and C, and GTPases such as Ras, Rab, and Rho (Kennedy et al. 2005). The list is continually growing, and the hundreds of implicated proteins form a complex signaling network whose contribution to LTP is still unclear (Bromberg et al. 2008).Signaling dynamics in neurons have traditionally been measured using biochemical analyses (Bromberg et al. 2008). However, the spatiotemporal resolution of conventional biochemistry is limited, restricting analysis to the time scale of many minutes and requiring the homogenization of tissue containing millions of synapses and other cellular elements. Furthermore, resolving synaptically induced changes in signaling by biochemical analysis typically requires stimulating many synapses at the same time, which may produce unintended effects, for instance, excitotoxicity or homeostatic plasticity.The size of dendritic spines is similar to the resolution of an optical microscope, permitting the optical analysis of biochemical signaling in each dendritic spine (Svoboda and Yasuda 2006). In particular, the advent of two-photon-based FRET techniques and the development of appropriate fluorescent reporters of specific biochemical reactions (see below) have provided readouts for signal transduction with high spatiotemporal resolution in live brain tissue (Svoboda and Yasuda 2006; Yasuda 2006). This has provided detailed information about the dynamics of signal transduction in spines and dendrites, and insights into the molecular mechanisms of synaptic plasticity.     

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.     

Neurogenesis in the Adult Avian Song-Control System

New neurons are added throughout the forebrain of adult birds. The song-control system is a model to investigate the addition of new long-projection neurons to a cortical circuit that regulates song, a learned sensorimotor behavior. Neuroblasts destined for the song nucleus HVC arise in the walls of the lateral ventricle, and wander through the pallium to reach HVC. The survival of new HVC neurons is supported by gonadally secreted testosterone and its downstream effectors including neurotrophins, vascularization, and electrical activity of postsynaptic neurons in nucleus RA (robust nucleus of the arcopallium). In seasonal species, the HVC→RA circuit degenerates in nonbreeding birds, and is reconstructed by the incorporation of new projection neurons in breeding birds. There is a functional linkage between the death of mature HVC neurons and the birth of new neurons. Various hypotheses for the function of adult neurogenesis in the song system can be proposed, but this remains an open question.Song behavior in oscine birds is regulated by a network of pallial and striatal nuclei. The song-control system shows extensive plasticity in adults, including ongoing neurogenesis in several nuclei (Brenowitz 2008). The addition of new neurons to the adult brain of higher vertebrates was first suggested by the pioneering studies of Altman and Das (1965) and Kaplan and Hinds (1977). They reported that labeled cells were present in the dentate gyrus (DG) of rats following the injection of ³H-thymidine. Their claims, however, met with skepticism and the neuronal identity of the new cells that they observed was called into question (Gross 2000). In an influential study, Rakic (1985) injected adult rhesus monkeys with ³H-thymidine and reported that, “all neurons of the rhesus monkey brain are generated during prenatal and early postnatal life.” The study of neuronal addition to the adult brain, was subsequently dropped for ∼20 years in the face of the dogma that neurogenesis was largely completed by birth (Gross 2000). This prevailing view only started to be overturned when Nottebohm and colleagues published a series of studies showing that new cells are added to the cortical-like song nucleus HVC (Fig. 1) of adult canaries (Serinus canarius) (Goldman and Nottebohm 1983). These new cells have neuronal morphology, some of these cells fire action potentials in response to sound (Paton and Nottebohm 1984), receive synaptic input (Burd and Nottebohm 1985), may synapse on neurons in the efferent robust nucleus of the arcopallium (RA) (Alvarez-Buylla et al. 1990), and express neuron-specific proteins (Barami et al. 1995). Together, these studies in songbirds showed that new neurons are born and incorporated into functional circuits in the brains of adults of higher vertebrates (Nottebohm 2004). This research on adult neurogenesis in songbirds stimulated investigators to re-examine this topic in mammals. It soon became clear that new neurons are added throughout life to the DG and olfactory bulb of mammals including humans (Cameron and Gould 1994; Gould et al. 1997, 1999a; Lim et al. 1997; Eriksson et al. 1998). Because of these initial confirmatory reports, there has been explosive growth in study of the mechanisms and functions of adult neurogenesis in the mammalian DG and olfactory bulb.Open in a separate windowFigure 1.A schematic of the neurogenic regions in the avian brain overlaid on the avian song circuits. Neurogenic regions are shown in red. Note the proximity of HVC (and hippocampus [HC]) to the ventricular zone (VZ). A schematic version of the motor pathway for song production is shown in blue. A schematic of the ascending auditory pathway is shown in green. The dotted line indicates an indirect route through many nuclei of the ascending auditory pathway leading to field L in the telencephalon. The anterior forebrain circuit for song learning and plasticity is shown in yellow. NCM, Caudomedial nidopallium; RA, arcopallium; LMAN, lateral magnocellular nucleus of the anterior neostriatum; OB, olfactory bulb; DLM, dorsolateral medial; PAm, parambigualis; RAm, retroambigualisBirds continue to be a productive model for the study of neurogenesis in the adult brain, as discussed below. In this article, we will focus on neurogenesis in the song-control system as this is the most intensively studied model in birds. (For a review of neurogenesis in the avian hippocampus [HC], see Barnea and Pravosudov 2011.) We will discuss the mechanisms of neurogenesis in the song system, intrinsic and extrinsic factors that influence neuronal addition, a linkage between cell death and neurogenesis, seasonal plasticity, and consider potential functions of adult neurogenesis.     

Self-avoidance and Tiling: Mechanisms of Dendrite and Axon Spacing

The spatial pattern of branches within axonal or dendritic arbors and the relative arrangement of neighboring arbors with respect to one another impact a neuron''s potential connectivity. Although arbors can adopt diverse branching patterns to suit their functions, evenly spread branches that avoid clumping or overlap are a common feature of many axonal and dendritic arbors. The degree of overlap between neighboring arbors innervating a surface is also characteristic within particular neuron types. The arbors of some populations of neurons innervate a target with a comprehensive and nonoverlapping “tiled” arrangement, whereas those of others show substantial territory overlap. This review focuses on cellular and molecular studies that have provided insight into the regulation of spatial arrangements of neurite branches within and between arbors. These studies have revealed principles that govern arbor arrangements in dendrites and axons in both vertebrates and invertebrates. Diverse molecular mechanisms controlling the spatial patterning of sister branches and neighboring arbors have begun to be elucidated.Axonal and dendritic arbors adopt complex and morphologically diverse shapes that influence neural connectivity and information processing. In this article we review anatomical and molecular studies that elucidate how the arrangements of branches within neuronal arbors are established during development (isoneuronal spacing) and how the relative spacing of arbors is determined when multiple neurons together innervate a defined territory (heteroneuronal spacing). Together these mechanisms ensure that arbors achieve functionally appropriate coverage of input or output territories.Isoneuronal and heteroneuronal processes display a variety of spacing arrangements, suggesting a diversity of underlying molecular mechanisms. Self-avoidance can occur between branches that arise from a single soma (Yau 1976; Kramer and Kuwada 1983; Kramer and Stent 1985), implying that neurons are able to discriminate “self,” which they avoid, from “nonself” arbors, with which they coexist (Kramer and Kuwada 1983). Similarly, arbors from different cells that share the same function and together innervate a defined territory can create a pattern of minimally overlapping neighboring dendritic or axonal fields, known as tiling. Such spacing mechanisms ensure that arbors maximize their spread across a territory while minimizing the redundancy with which the territory is innervated. In contrast, adhesive interactions between arbors can operate to maintain coherence of dendrites at specific targets (Zhu and Luo 2004), or to bundle functionally similar processes and possibly coordinate their activity (Campbell et al. 2009). Understanding how processes are patterned relative to one another can help to uncover the functional logic of neural circuit organization.Here we focus primarily on mechanisms of isoneuronal and heteroneuronal avoidance that result in complete and nonredundant innervation of sensory or synaptic space. Such mechanisms have been studied extensively in systems where neuronal arbors innervate a two-dimensional plane, such as the retina or body wall (Wassle et al. 1981; Perry and Linden 1982; Hitchcock 1989; Lin and Masland 2004; Fuerst et al. 2009; Kramer and Stent 1985; Grueber et al. 2003; Sugimura et al. 2003; Sagasti et al. 2005). However, the principles regulating process spacing in these regions likely also apply in three dimensions, most prominently where processes are segregated into nonoverlapping domains or columns (Huckfeldt et al. 2009). It is also notable that nonneuronal cell types might similarly engage in self-avoidance and form tiling arrangements, including leech comb cells (Jellies and Kristan 1991) and mammalian astrocytes (Bushong et al. 2002; Ogata and Kosaka 2002; Livet et al. 2007). Elucidating the mechanisms of process spacing during development is therefore relevant for understanding principles of tissue organization inside and outside of the nervous system.     

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.     

mGluR1/TRPC3-mediated Synaptic Transmission and Calcium Signaling in Mammalian Central Neurons

Metabotropic glutamate receptors type 1 (mGluR1s) are required for a normal function of the mammalian brain. They are particularly important for synaptic signaling and plasticity in the cerebellum. Unlike ionotropic glutamate receptors that mediate rapid synaptic transmission, mGluR1s produce in cerebellar Purkinje cells a complex postsynaptic response consisting of two distinct signal components, namely a local dendritic calcium signal and a slow excitatory postsynaptic potential. The basic mechanisms underlying these synaptic responses were clarified in recent years. First, the work of several groups established that the dendritic calcium signal results from IP₃ receptor-mediated calcium release from internal stores. Second, it was recently found that mGluR1-mediated slow excitatory postsynaptic potentials are mediated by the transient receptor potential channel TRPC3. This surprising finding established TRPC3 as a novel postsynaptic channel for glutamatergic synaptic transmission.Glutamate is the predominant neurotransmitter used by excitatory synapses in the mammalian brain (Hayashi 1952; Curtis et al. 1959). At postsynaptic sites, glutamate binds to two different classes of receptors, namely the ionotropic glutamate receptors (iGluRs) and the metabotropic glutamate receptors (mGluRs) (Sladeczek et al. 1985; Nicoletti et al. 1986; Sugiyama et al. 1987). The iGluRs represent ligand-gated nonselective cation channels that underlie excitatory postsynaptic currents (EPSCs). Based on their subunit composition, gating, and permeability properties, they are subdivided into three groups named after specific agonists: AMPA- (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid), NMDA receptors (N-methyl D-aspartate receptors) and kainate receptors (Alexander et al. 2009). The other class of glutamate receptors, the mGluRs, consists of receptors that are coupled to G proteins and act through distinct downstream signaling cascades. They are structurally different from iGluRs and characterized by the presence of seven transmembrane domains (Houamed et al. 1991; Masu et al. 1991). The mGluRs exist as homodimers that do not by themselves form an ion-permeable pore in the membrane (Ozawa et al. 1998). To date, eight different genes (and more splice variants) encoding mGluRs have been identified and form the mGluR1 through mGluR8 subtypes (Alexander et al. 2009). Based on the amino acid sequence homology, downstream signal transduction pathways, and pharmacological properties, each of the subtypes was assigned to one of three groups. Group I receptors consist of mGluR1 and mGluR5 that positively couple to the phospholipase C (PLC). The receptors mGluR2 and mGluR3 constitute group II, whereas the remaining mGluRs, namely mGluR4, mGluR6, mGluR7, and mGluR8, belong to group III. Both groups II and III inhibit the adenylyl cyclase and thereby reduce the concentration of cAMP in the cytosol.Of all different subtypes, mGluR1 is the most abundantly expressed mGluR in the mammalian central nervous system. In the brain, mGluR1 is highly expressed in the olfactory bulb, dentate gyrus, and cerebellum (Lein et al. 2007). The highest expression level of mGluR1 in the brain is found in Purkinje cells, the principal neurons of the cerebellar cortex (Shigemoto et al. 1992; Lein et al. 2007). Together with the AMPA receptors, mGluR1s are part of the excitatory synapses formed between parallel fibers and Purkinje cells (Fig. 1A). Each Purkinje cell is innervated by 100,000–200,000 parallel fibers (Ito 2006) that are axons of the cerebellar granule cells, the most abundant type of neuron in the brain. A second type of excitatory input to Purkinje cells is represented by the climbing fibers that originate in the inferior olive in the brain stem (Ito 2006). The two excitatory synaptic inputs to Purkinje cells are important determinants for the main functions of the cerebellum, including the real-time control of movement precision, error-correction, and control of posture as well as the procedural learning of complex movement sequences and conditioned responses.Open in a separate windowFigure 1.Parallel fiber-evoked mGluR1-dependent signals. (A) Diagram showing the parallel fiber synaptic input to Purkinje cell dendrites. (B) Microelectrode recording of glutamatergic postsynaptic potentials from a Purkinje cell in an acute slice of adult rat cerebellum. Short trains of stimuli to the parallel fibers (5–6 at 50 Hz) caused summation of the early AMPA receptor-dependent EPSPs (leading to spike firing) and a slow, delayed, depolarizing potential (slow EPSP), which was reversibly inhibited by antagonist of mGluRs (+)-MCPG (1mM). (C) Confocal image of a patch-clamped Purkinje cell in a cerebellar slice of an adult mouse. The patch-clamp pipette and the glass capillary used for electrical stimulation of parallel fibers are depicted schematically. The site of stimulation is shown at higher magnification in D. (D) Left: Parallel fiber-evoked (five pulses at 200 Hz, in 10 mM CNQX) synaptic responses consisting of a dendritic mGluR1-dependent Ca²⁺ transient (ΔF/F, top) and an early rapid and a slow excitatory postsynaptic current (EPSC, bottom). Block of the mGluR1-dependent components by the group I-specific mGluR-antagonist CPCCOEt (200 µM) is shown as indicated. Right: Pseudocolor image of the synaptic Ca²⁺ signal. (B, Reprinted with modifications, with permission, from Batchelor and Gaithwaite 1997 [Nature Publishing Group].)It is expected that mGluR1 is involved in many of these cerebellar functions. This view is supported by the observation that mGluR1-deficient knockout mice show severe impairments in motor coordination. In particular, the gait of these mice is strongly affected as well as their ability for motor learning and general coordination (Aiba et al. 1994). The phenotype of the general mGluR1-knockout mice is rescued by the insertion of the gene encoding mGluR1 exclusively into cerebellar Purkinje cells (Ichise et al. 2000) and blockade of mGluR1 expression only in Purkinje cells of adult mice leads to impaired motor coordination (Nakao et al. 2007). These findings established mGluR1 in Purkinje cell as synaptic receptors that are indispensable for a normal cerebellar function.Synaptic transmission involving mGluR1s is found at both parallel fiber-Purkinje cell synapses (Batchelor and Garthwaite 1993; Batchelor et al. 1994) as well as at climbing fiber-Purkinje cell synapses (Dzubay and Otis 2002). Most of our knowledge on the mGluR1 was gained from the analysis of the parallel fiber synapses. The parallel fiber synapse is quite unique in the central nervous system regarding its endowment with neurotransmitter receptors. In contrast to most other glutamatergic synapses in the mammalian brain, it lacks functional NMDA receptors (Shin and Linden 2005). The entire synaptic transmission at these synapses relies on AMPA receptors and on mGluR1 (Takechi et al. 1998). Although AMPA receptors are effectively activated even with single shock stimuli (Konnerth et al. 1990; Llano et al. 1991b), activation of mGluRs requires repetitive stimulation (Batchelor and Garthwaite 1993; Batchelor et al. 1994; Batchelor and Garthwaite 1997; Takechi et al. 1998). A possible explanation for the need of repetitive stimulation may relate to the observation that mGluR1s are found mostly at the periphery of the subsynaptic region (Nusser et al. 1994). At these sites outside the synaptic cleft, glutamate levels that are sufficiently high for receptor activation may be reached only with repetitive stimulation.At parallel fiber-Purkinje cell synapses, repetitive stimulation produces an initial AMPA receptor postsynaptic signal component, followed by a more prolonged mGluR1 component (Fig. 1). Figure 1B shows a current clamp recording of this response consisting of an early burst of action potentials, followed by a prolonged depolarization known as a “slow excitatory postsynaptic potential” (slow EPSP) (Batchelor and Garthwaite 1993; Batchelor et al. 1994; Batchelor and Garthwaite 1997). Voltage-clamp recordings allow a clear separation of the initial rapid, AMPA receptor mediated excitatory postsynaptic current (EPSC) and the mGluR1-mediated slow EPSC (Fig. 1D) (Takechi et al. 1998; Hartmann et al. 2008). In addition of inducing the slow EPSPs, mGluR1s mediate a large and highly localized dendritic calcium transient in cerebellar Purkinje cells (Fig. 1D) (Llano et al. 1991a; Finch and Augustine 1998; Takechi et al. 1998).     

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.     

Sexual Conflict Arising from Extrapair Matings in Birds

The discovery that extrapair copulation (EPC) and extrapair paternity (EPP) are common in birds led to a paradigm shift in our understanding of the evolution of mating systems. The prevalence of extrapair matings in pair-bonded species sets the stage for sexual conflict, and a recent focus has been to consider how this conflict can shape variation in extrapair mating rates. Here, we invert the causal arrow and consider the consequences of extrapair matings for sexual conflict. Extrapair matings shift sexual conflict from a simple two-player (male vs. female) game to a game with three or more players, the nature of which we illustrate with simple diagrams that highlight the net costs and benefits of extrapair matings to each player. This approach helps identify the sorts of traits that might be under selection because of sexual conflict. Whether EPP is driven primarily by the extrapair male or the within-pair female profoundly influences which players are in conflict, but the overall pattern of conflict varies little among different mating systems. Different aspects of conflict are manifest at different stages of the breeding cycle and can be profitably considered as distinct episodes of selection caused by conflict. This perspective is illuminating both because conflict between specific players can change across episodes and because the traits that evolve to mediate conflict likely differ between episodes. Although EPP clearly leads to sexual conflict, we suggest that the link between sexual conflict and multiple paternity might be usefully understood by examining how deviations from lifetime sexual monogamy influence sexual conflict.The development of genetic tools for determining parentage fundamentally altered our understanding of animal mating systems (Jeffreys et al. 1985; Avise 1996; Reynolds 1996) and provided invaluable insights into the consequences and causes of females mating with more than one male. Particularly for the study of birds, these methods revealed that social pair bonds often fail to match the actual patterns of copulations that produced offspring (Gowaty and Karlin 1984; Birkhead and Møller 1992; Reynolds 1996; Petrie and Kempenaers 1998), revolutionizing the study of avian mating systems. Extensive research and two recent reviews point out the progress we have made in this field and show how little we still understand extrapair behavior (Griffith et al. 2002; Westneat and Stewart 2003).In the 1960s, David Lack compiled what was then known about mating systems in birds and concluded that >90% of species were monogamous, a pattern that provided an early framework for the development of mating system theory (Lack 1968; Orians 1969; Emlen and Oring 1977). When it was later discovered that sexual mating patterns did not match the social mating systems that Lack described, the field was turned on its head (Westneat et al. 1990; Avise 1996; Reynolds 1996; Zeh and Zeh 2001). In extreme cases, the mismatch between the social and sexual mating systems is nothing short of spectacular; in fairywrens (Malurus species) that are socially monogamous, cooperatively breeding species with helpers, the extrapair paternity (EPP) rate can exceed 75% of all offspring and 95% of all broods (Mulder et al. 1994). In socially monogamous birds, in general, the rate of EPP is typically on the order of 10% of offspring and 20% of broods (Griffith et al. 2002), but variation among species, and even populations within species, is extensive (Arnold and Owens 2002; Griffith et al. 2002). The occurrence of EPP has profound consequences for the evolution of social behavior, both because it alters the scope for the action of sexual selection (Webster et al. 1995; Sheldon and Ellegren 1999) and because it results in males often providing parental care to offspring they have not sired (Davies et al. 1992; Westneat and Sherman 1993).Even in taxa with mating systems other than social monogamy, or in which there is no obvious pair bond, the ability to determine parentage genetically was revolutionary, allowing precise estimates of male reproductive success when females mate multiply. That focus on multiple mating also catalyzed an interest in sexual selection from the female’s perspective, whereas previous attention had been strongly biased toward males and male traits. More specifically, it raised the questions as to why females would pursue and benefit from matings outside the social pair bond (Westneat et al. 1990; Petrie and Kempenaers 1998), and why a female would benefit from mating with more than one male for a given clutch or litter. This new focus on females brought attention to the issue of polyandry more generally (Jennions and Petrie 2000; Simmons 2005; Parker and Birkhead 2013; Pizzari and Wedell 2013).Recently, the assumption that females control mating patterns, and thus that polyandry and EPP can be universally understood from the perspective of fitness benefits to females, has been questioned (Westneat and Stewart 2003). Focusing specifically on EPP, Westneat and Stewart (2003) suggested that, in some taxa, EPP could be driven entirely by benefits to the extrapair-seeking male. They also suggested that many aspects of EPP can be profitably explored from the perspective of sexual conflict, as had Petrie and Kempenaers (1998) before them. Previous interest in the relation between EPP and sexual conflict in birds was focused particularly on trying to explain the incidence and frequency of EPP within and among species. Westneat and Stewart (2003) recognized that that link was indirect. Instead, they suggested that sexual conflict theory might help us to identify traits that could arise from conflict and that those traits might inform the search for a general explanation of the huge variation in EPP rates both among and within bird species.Sexual conflict, the conflicting fitness interests of males and females during mating (Parker 1979; Rice 1998; Arnqvist and Rowe 2005), can lead to antagonistic coevolution between the traits expressed in males and those expressed in females, traits that in some way influence mating outcomes. Traits in males and females are ultimately the drivers of conflict, and, reciprocally, conflict fuels further trait evolution. Sexual conflict theory is useful because it can potentially explain the evolution and maintenance of traits that are otherwise difficult to understand (Arnqvist and Rowe 2005). Thus, studies often examine the factors and traits that underlie different aspects of sexual conflict, as well as the types of morphological and behavioral traits that result from selection caused by the sexual conflict itself.In this article, we build on the foundation provided by Westneat and Stewart (2003). They proposed that sexual conflict can help to explain variation in the occurrence of EPP among species and populations (Westneat and Stewart 2003). Here, we invert the focus and seek to understand the consequences that EPP can have for sexual conflict and the relation between EPP and other drivers of sexual conflict. Thus, we examine the players involved in the sexual conflict generated by EPP and the costs and benefits that underpin the conflicts among the different players. We point out that different conflicts are involved in the different stages of a single bout of reproduction, and we suggest that these represent sequential periods of conflict, each of which is a different episode of selection generated from that conflict. We then place these patterns of conflict into a broader context by contrasting how different patterns of fidelity and infidelity (including EPP) during a lifetime of mating can influence sexual conflict. Our review focuses on birds as examples, both because they have been extensively studied with respect to EPP and because they have been the subjects of most of our own research. Our goal, however, is to provide a framework for understanding trait evolution under the influence of sexual conflict caused by females mating multiply in any animal species.     

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).     

Memory Consolidation

Conscious memory for a new experience is initially dependent on information stored in both the hippocampus and neocortex. Systems consolidation is the process by which the hippocampus guides the reorganization of the information stored in the neocortex such that it eventually becomes independent of the hippocampus. Early evidence for systems consolidation was provided by studies of retrograde amnesia, which found that damage to the hippocampus-impaired memories formed in the recent past, but typically spared memories formed in the more remote past. Systems consolidation has been found to occur for both episodic and semantic memories and for both spatial and nonspatial memories, although empirical inconsistencies and theoretical disagreements remain about these issues. Recent work has begun to characterize the neural mechanisms that underlie the dialogue between the hippocampus and neocortex (e.g., “neural replay,” which occurs during sharp wave ripple activity). New work has also identified variables, such as the amount of preexisting knowledge, that affect the rate of consolidation. The increasing use of molecular genetic tools (e.g., optogenetics) can be expected to further improve understanding of the neural mechanisms underlying consolidation.Memory consolidation refers to the process by which a temporary, labile memory is transformed into a more stable, long-lasting form. Memory consolidation was first proposed in 1900 (Müller and Pilzecker 1900; Lechner et al. 1999) to account for the phenomenon of retroactive interference in humans, that is, the finding that learned material remains vulnerable to interference for a period of time after learning. Support for consolidation was already available in the facts of retrograde amnesia, especially as outlined in the earlier writings of Ribot (1881). The key observation was that recent memories are more vulnerable to injury or disease than remote memories, and the significance of this finding for consolidation was immediately appreciated.

In normal memory a process of organization is continually going on—a physical process of organization and a psychological process of repetition and association. In order that ideas may become a part of permanent memory, time must elapse for these processes of organization to be completed. (Burnham 1903, p. 132)

It is useful to note that the term consolidation has different contemporary usages that derive from the same historical sources. For example, the term is commonly used to describe events at the synaptic/cellular level (e.g., protein synthesis), which stabilize synaptic plasticity within hours after learning. In contrast, systems consolidation, which is the primary focus of this review, refers to gradual reorganization of the brain systems that support memory, a process that occurs within long-term memory itself (Squire and Alvarez 1995; Dudai and Morris 2000; Dudai 2012).Systems consolidation is typically, and accurately, described as the process by which memories, initially dependent on the hippocampus, are reorganized as time passes. By this process, the hippocampus gradually becomes less important for storage and retrieval, and a more permanent memory develops in distributed regions of the neocortex. The idea is not that memory is literally transferred from the hippocampus to the neocortex, for information is encoded in the neocortex as well as in hippocampus at the time of learning. The idea is that gradual changes in the neocortex, beginning at the time of learning, establish stable long-term memory by increasing the complexity, distribution, and connectivity among multiple cortical regions. Recent findings have enriched this perspective by emphasizing the dynamic nature of long-term memory (Dudai and Morris 2013). Memory is reconstructive and vulnerable to error, as in false remembering (Schacter and Dodson 2001). Also, under some conditions, long-term memory can transiently return to a labile state (and then gradually stabilize), a phenomenon termed reconsolidation (Nader et al. 2000; Sara 2000; Alberini 2005). In addition, the rate of consolidation can be influenced by the amount of prior knowledge that is available about the material to be learned (Tse et al. 2007; van Kesteren et al. 2012).Neurocomputational models of consolidation (McClelland et al. 1995; McClelland 2013) describe how the acquisition of new knowledge might proceed and suggest a purpose for consolidation. As originally described, elements of information are first stored in a fast-learning hippocampal system. This information directs the training of a “slow learning” neocortex, whereby the hippocampus gradually guides the development of connections between the multiple cortical regions that are active at the time of learning and that represent the memory. Training of the neocortex by the hippocampus (termed “interleaved” training) allows new information to be assimilated into neocortical networks with a minimum of interference. In simulations (McClelland et al. 1995), rapid learning of new information, which was inconsistent with prior knowledge, was shown to cause interference and disrupt previously established representations (“catastrophic interference”). The gradual incorporation of information into the neocortex during consolidation avoids this problem. In a recent revision of this framework (McClelland 2013), neocortical learning is characterized, not so much as fast or slow, but as dependent on prior knowledge. If the information to be learned is consistent with prior knowledge, neocortical learning can be more rapid.This review considers several types of evidence that illuminate the nature of the consolidation process: studies of retrograde amnesia in memory-impaired patients, studies of healthy volunteers with neuroimaging, studies of sleep and memory, studies of experimental animals, both with lesions or other interventions, and studies that track neural activity as time passes after learning.     

Retrograde Traffic from the Golgi to the Endoplasmic Reticulum

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

Earth��s Earliest Atmospheres

Earth is the one known example of an inhabited planet and to current knowledge the likeliest site of the one known origin of life. Here we discuss the origin of Earth’s atmosphere and ocean and some of the environmental conditions of the early Earth as they may relate to the origin of life. A key punctuating event in the narrative is the Moon-forming impact, partly because it made Earth for a short time absolutely uninhabitable, and partly because it sets the boundary conditions for Earth’s subsequent evolution. If life began on Earth, as opposed to having migrated here, it would have done so after the Moon-forming impact. What took place before the Moon formed determined the bulk properties of the Earth and probably determined the overall compositions and sizes of its atmospheres and oceans. What took place afterward animated these materials. One interesting consequence of the Moon-forming impact is that the mantle is devolatized, so that the volatiles subsequently fell out in a kind of condensation sequence. This ensures that the volatiles were concentrated toward the surface so that, for example, the oceans were likely salty from the start. We also point out that an atmosphere generated by impact degassing would tend to have a composition reflective of the impacting bodies (rather than the mantle), and these are almost without exception strongly reducing and volatile-rich. A consequence is that, although CO- or methane-rich atmospheres are not necessarily stable as steady states, they are quite likely to have existed as long-lived transients, many times. With CO comes abundant chemical energy in a metastable package, and with methane comes hydrogen cyanide and ammonia as important albeit less abundant gases.The origin of life has not been seen in Earth’s rock record, and poor preservation of Earth’s oldest rocks suggests that it will not be. The oldest bits of rock that might plausibly retain geochemical hints of habitable conditions on Earth’s surface—a handful of zircons—have been subject to fierce debates regarding whether they contain such evidence. However, the weight of evidence does suggest that Earth has supported microbial life since the Hadean (“Hadean” refers to the geologic Eon preceding the Achaean. It can be regarded as Earth before the appearance of a true-rock record 3.9 Ga—the precise definition remains to be agreed on by the proper authorities). This would make Hadean Earth the one known planet where life has begun.The modern focus on the atmosphere as the source of prebiotic chemistry dates to the famous Miller-Urey experiments of the 1950s (Miller 1953, 1955; Miller and Urey 1959; Oró and Kamel 1961; Johnson et al. 2008). These experiments were intended to model the kinds of disequilibrium chemistry that would have resulted from electrical discharges in, or ultraviolet radiation being absorbed in, highly reduced atmospheres in which methane, ammonia, and water were all major constituents. These experiments were driven by Harold C. Urey’s theory that Earth accreted as a cool body and that its atmosphere was dominated by hydrogen and the hydrides of common volatiles (Urey won the Nobel Prize for Chemistry in 1934 for the discovery of deuterium). Miller and his colleagues, and many other investigators who have since performed similar experiments, have consistently found that a wide range of amino acids and other prebiotically interesting molecules form readily in such environments (e.g., see the review by Oró et al. 1990). These experiments were very influential in directing the attention of prebiotic chemists to a highly reduced primordial atmosphere.However, photochemical studies showed that any methane (Lasaga et al. 1971) or ammonia (Kuhn and Atreya 1979; Kasting 1982) in the atmosphere would quickly be destroyed. Meanwhile geologically based arguments, which treat the atmosphere as outgassed from the solid Earth, were taken as strongly suggesting that Earth’s original atmosphere was composed mostly of H₂O, CO₂, and N₂, with only small amounts of CO and H₂, and essentially no CH₄ or NH₃ (Poole 1951; Holland 1962; Abelson 1966; Holland 1984). This composition of volcanic gases is determined by temperature and the QFM (quartz-fayalite-magnetite) mineral buffer pertinent to the modern mantle. Nor is there evidence of a time on Earth when things were clearly different. Geochemical evidence in Earth’s oldest igneous rocks indicates that the redox state of the Earth’s mantle has not changed over the past 3.8 Gyr (Delano 2001; Canil 2002). Miller-Urey-type experiments performed in the more oxidized mixtures of modern volcanic gases generate relatively little of prebiotic interest, especially when CO₂ is abundant (Miller and Urey 1959; Schlessinger and Miller 1983; Stribling and Miller 1987). New work suggests that spark yields of ammonia, HCN, and amino acids in CO₂-N2-water mixtures can be less disappointing if the water is allowed to become acidic (Cleaves et al. 2008). Nevertheless, the contrast between methane and ammonia on the one hand and carbon dioxide and dinitrogen on the other led many prebiotic chemists, Miller and Urey prominent among them, to regard the presence of life on Earth as providing a strong boundary condition on the nature of Earth’s early atmosphere.The sense of poor prospects led some to abandon the atmosphere in favor of the hydrosphere. At the low temperatures and high water activities of hydrothermal systems, it is in theory possible to get non-negligable amounts of methane and ammonia at the QFM buffer (French 1966; Shock and Schulte 1990, 1998). Shock and Schulte (1990) used this approach to explain the abundances of organic molecules in asteroids (as sampled by carbonaceous meteorites) and suggested that such a model might have application to the origin of life on Earth (Shock 1990; Shock et al. 1995; Shock and Schulte 1998). The issue of a submarine (as opposed to a subaerial) origin of life became contentious (Miller and Bada 1988, 1993; Shock and Schulte 1993). Significant features of the hydrothermal hypothesis are that (1) it ties the origin of life to the process of making organic molecules, and (2) it implies that life is widespread in the Solar System, because hydrothermal systems may exist in many moons (Shock and McKinnon 1993).Another workaround is to abandon the idea that organic molecules were generated in situ here on Earth. Instead the organic molecules would be delivered by comets and asteroids and interplanetary dust particles (IDPs, Anders 1989; Chyba and Sagan 1992; Whittet 1997). The basis of this proposal is that organic molecules are abundant in the Solar System. Many meteorites and dust grains are rich in complex organic molecules, and there is little doubt that comets are at least as rich. The chief difficulty is that, apart from special cases, only a small fraction of the more interesting and more delicate organic materials in comets and asteroids would survive impact (Clark 1988; Anders 1989; Chyba et al. 1990; Chyba and Sagan 1992; Whittet 1997; Pierazzo and Chyba 1999; Pasek and Lauretta 2008). The importance of an exogenic source of organics to the origin of life has probably been overstated. In the median case the quantities aren’t large and the biological potential of a modest cosmic windfall of IDPs is unclear, although a slow soft collision by a big organic-rich comet—possible but by construction unlikely—could have a huge unique effect (Clark 1988). An alternative lesson to be taken from abundant organics in the Solar System is that organic molecules are not hard to make, and so were probably also made here.A third perspective to the origin of the atmosphere—that the earliest atmosphere was degassed from impacting material as it arrived rather than outgassed from the solid Earth into a primordial vacuum (Arrhenius et al. 1974; Lange et al. 1985; Tyburczy et al. 1986; Abe and Matsui 1986; Zahnle et al. 1988; Ahrens et al. 1989)—has gotten comparatively little traction. Recently three new theoretical studies (Schaefer and Fegley 2007, 2010; Hashimoto et al. 2007) show that atmospheres dominated by impact degassing would be much more reduced than atmospheres dominated by Earth’s mantle. A fourth recent study (Sugita and Schultz 2009) addresses impact degassing and impact synthesis in possible cometary matter experimentally. The latter can be regarded as parallel to the experiments performed by nature when the pieces of comet Shoemaker-Levy 9 struck Jupiter in July 1994. The SL9 impacts generated vast quantities of small molecules, especially CO, but the list of apparently synthetic products also included HCN, C₂H₂, C₂H₄, S₂, CS, CS₂, OCS, and CO₂ (Zahnle et al. 1995; Harrington et al. 2004).Here we address the state and properties of Earth’s primordial atmosphere. Our review is presented in three parts: the origin of the atmosphere, the Moon-forming impact, and events taking place after the Moon-forming impact. Placing the origin of the atmosphere before the Moon-forming impact is a choice that is founded on the high volatile contents of all known chondritic meteorites: To build Earth without volatiles is difficult if all known examples of possible source materials are more volatile-rich than Earth. Nonetheless we will also consider the alternative—volatile delivery after the Moon-forming impact—because it is one of the concepts in debate (cf. Albarède 2009) and because the hypothesis of transient, strongly reduced impact-degassed atmospheres applies obviously and directly to it.     

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).