Murine Mammary Epithelial Stem Cells: Discovery,Function, and Current Status

An entire mammary epithelial outgrowth, capable of full secretory differentiation, may comprise the progeny of a single cellular antecedent, i.e., may be generated from a single mammary epithelial stem cell. Early studies showed that any portion of an intact murine mammary gland containing epithelium could recapitulate an entire mammary epithelial tree on transplantation into an epithelium-free mammary fat pad. More recent studies have shown that a hierarchy of mammary stem/progenitor cells exists among the mammary epithelium and that their behavior and maintenance is dependent on signals generated both locally and systemically. In this review, we have attempted to develop the scientific saga surrounding the discovery and characterization of the murine mammary stem/progenitor cell hierarchy and to suggest further approaches that will enhance our knowledge and understanding of these cells and their role in both normal development and neoplasia.Before the 1980s there was little if any thought that the epithelium in murine mammary glands might be engendered by or supported by a mammary epithelial specific stem cell. In 1980, Rudland et al. wrote a review entitled “Stem cells in rat mammary development and cancer: A review” and noted that dimethylbenz [α] anthracene (DMBA)-induced rat carcinomas contained all three main types of epithelium found in the normal rat gland, those lining the ductal lumina, those lining the alveolar lumina, and myoepithelial cells (Rudland et al. 1980). They suggested, based on the two types of morphologically distinct epithelial (luminal and myoepithelial) cancer cells in the clonally derived Rama 25 cell line, that a single cell might give rise to both types and this also held true when these cells were inoculated into hosts and produced tumors. Williams and Daniel (Williams and Daniel 1983) suggested that the cap cells at the tip of the growing ducts in the mouse could give rise to both luminal and myoepithelial cells during ductal morphogenesis. However, no direct evidence that a single cell could produce both epithelial cell types in vivo was available. Nevertheless, in retrospect there was evidence that full regenerative activity for mammary epithelial existed in every part of the adult mammary epithelial tree.The experiments that originally showed the potential existence of stem cells in the mouse mammary gland were the pioneering studies of DeOme and his students, Les Faulkin and Charles Daniel. The approach they developed and optimized was serial transplantation of normal mammary gland into the cleared mammary fat pad of syngeneic mice (Deome et al. 1959; Faulkin and Deome 1960). The cleared mammary fat pad allowed the transplantation and growth of normal mammary cells into their normal anatomical site and under the influence of a normal physiological environment. Using this method, DeOme and coworkers showed that all portions of the normal mammary gland contains cells that will grow and fill the fat pad with a normal ductal mammary tree and respond to hormones with a normal differentiation program (Daniel 1975; Daniel et al. 1975). The progeny of the transplanted cells could be serially transplanted into the appropriate recipients for multiple times; however, unlike preneoplastic or neoplastic cells, the normal cells always senesced after multiple serial transplants, generally five to eight transplant generations (Daniel 1975). This was interpreted as indicating mammary stem cells possessed a finite proliferative activity (i.e., life span). This finite life span was a fundamental difference between normal and preneoplastic/neoplastic mammary cells. Cells with an indefinite in vivo life span (i.e., immortalized) have been identified in numerous mammary model systems, including MMTV-induced alveolar hyperplasia''s (Callahan and Smith 2000), chemical carcinogen-induced ductal and alveolar hyperplasia''s (Smith et al. 1978, 1980), hormonally induced alveolar hyperplasia, spontaneously immortalized ductal hyperplasia''s (Medina 2000, 2002), and cells containing specific genetic alterations (i.e., p53 deletion, Polyoma mT antigen) (Maglione et al. 2001; Medina et al. 2002).Subsequent studies showed that stem cells were located along the entire mammary tree and represented in all the different developmental states of the mammary gland. These stages included primary and tertiary ducts from 6- and 16-wk virgin glands, uniparous and multiparous regressed gland, 15-d pregnant and 10-d lactating glands (Smith and Medina 1988). Host age and reproductive history had little influence on the frequency of stem cells as measured by percent successful takes and life span assay (Young et al. 1971; Smith and Medina 1988). Mammary cells taken from 26-mo-old virgin mice had the same transplant potential as cells taken from 3-wk-old mice. Cell populations, from both, senesced after five transplant generations. Similarly, mammary cells in 12-mo-old multiparous mice had the same serial transplant potential as cells from 3-wk-old virgin mice (Young et al. 1971). Finally, continuous hormone stimulation did not induce additional loss of ductal growth potential. These results have important implications for understanding the role of mammary stem cells in normal mammary development because they emphasize that the mammary stem cell is a relatively quiescent cell that is only activated under conditions of gland repopulation (i.e., fetal growth stage and pubertal growth phase).     

Cadherin-mediated Intercellular Adhesion and Signaling Cascades Involving Small GTPases

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

Molecular Mechanisms of Fibroblast Growth Factor Signaling in Physiology and Pathology

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

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).     

Origin of Microglia: Current Concepts and Past Controversies

Microglia are the resident macrophages of the central nervous system (CNS), which sit in close proximity to neural structures and are intimately involved in brain homeostasis. The microglial population also plays fundamental roles during neuronal expansion and differentiation, as well as in the perinatal establishment of synaptic circuits. Any change in the normal brain environment results in microglial activation, which can be detrimental if not appropriately regulated. Aberrant microglial function has been linked to the development of several neurological and psychiatric diseases. However, microglia also possess potent immunoregulatory and regenerative capacities, making them attractive targets for therapeutic manipulation. Such rationale manipulations will, however, require in-depth knowledge of their origins and the molecular mechanisms underlying their homeostasis. Here, we discuss the latest advances in our understanding of the origin, differentiation, and homeostasis of microglial cells and their myelomonocytic relatives in the CNS.Microglia are the resident macrophages of the central nervous system (CNS), which are uniformly distributed throughout the brain and spinal cord with increased densities in neuronal nuclei, including the Substantia nigra in the midbrain (Lawson et al. 1990; Perry 1998). They belong to the nonneuronal glial cell compartment and their function is crucial to maintenance of the CNS in both health and disease (Ransohoff and Perry 2009; Perry et al. 2010; Ransohoff and Cardona 2010; Prinz and Priller 2014).Two key functional features define microglia: immune defense and maintenance of CNS homeostasis. As part of the innate immune system, microglia constantly sample their environment, scanning and surveying for signals of external danger (Davalos et al. 2005; Nimmerjahn et al. 2005; Lehnardt 2010), such as those from invading pathogens, or internal danger signals generated locally by damaged or dying cells (Bessis et al. 2007; Hanisch and Kettenmann 2007). Detection of such signals initiates a program of microglial responses that aim to resolve the injury, protect the CNS from the effects of the inflammation, and support tissue repair and remodeling (Minghetti and Levi 1998; Goldmann and Prinz 2013).Microglia are also emerging as crucial contributors to brain homeostasis through control of neuronal proliferation and differentiation, as well as influencing formation of synaptic connections (Lawson et al. 1990; Perry 1998; Hughes 2012; Blank and Prinz 2013). Recent imaging studies revealed dynamic interactions between microglia and synaptic connections in the healthy brain, which contributed to the modification and elimination of synaptic structures (Perry et al. 2010; Tremblay et al. 2010; Bialas and Stevens 2013). In the prenatal brain, microglia regulate the wiring of forebrain circuits, controlling the growth of dopaminergic axons in the forebrain and the laminar positioning of subsets of neocortical interneurons (Squarzoni et al. 2014). In the postnatal brain, microglia-mediated synaptic pruning is similarly required for the remodeling of neural circuits (Paolicelli et al. 2011; Schafer et al. 2012). In summary, microglia occupy a central position in defense and maintenance of the CNS and, as a consequence, are a key target for the treatment of neurological and psychiatric disorders.Although microglia have been studied for decades, a long history of experimental misinterpretation meant that their true origins remained debated until recently. Although we knew that microglial progenitors invaded the brain rudiment at very early stages of embryonic development (Alliot et al. 1999; Ransohoff and Perry 2009), it has now been established that microglia arise from yolk sac (YS)-primitive macrophages, which persist in the CNS into adulthood (Davalos et al. 2005; Nimmerjahn et al. 2005; Ginhoux et al. 2010, 2013; Kierdorf and Prinz 2013; Kierdorf et al. 2013a). Moreover, early embryonic brain colonization by microglia is conserved across vertebrate species, implying that it is essential for early brain development (Herbomel et al. 2001; Bessis et al. 2007; Hanisch and Kettenmann 2007; Verney et al. 2010; Schlegelmilch et al. 2011; Swinnen et al. 2013). In this review, we will present the latest findings in the field of microglial ontogeny, which provide new insights into their roles in health and disease.     

Molecular Bases of Cell–Cell Junctions Stability and Dynamics

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

On Stem Cells in the Human Breast

In the human breast, stem cells give rise to myoepithelial and luminal epithelial cells that are needed during monthly estrous cycles and lactation. The mechanisms that govern mammary stem cells are hotly debated.Petersen and Polyak (2011) elegantly explain the developmental hierarchy of the human mammary gland as it is currently understood. It is amazing that the small pool of stem cells can be cyclically called on to give rise to the progenitors and more differentiated myoepithelial and luminal epithelial cells that are needed for expansion during monthly estrous cycles and in preparation for lactation. How do the stem cells respond so perfectly and repetitively throughout a woman’s childbearing years? Do stem cells harbor internal circadian clocks that work in time with similar clocks in the endocrine system and ovaries? Or are mammary stem cells able to respond to shifting physiological needs of the organism because their functions are controlled by their microenvironment, which changes with the ebb and flow of the physiological tide? That estrous cycles can vary according to life’s circumstances (e.g., changes in nutrition, exercise, or stress) and because lengths of pregnancies and lactation periods differ for each pregnancy, it seems likely that mammary stem cells are governed by an external control mechanism that interacts with systemic changes in physiology.That stem cells and all of their progeny share identical genomes, and that stem cells reside inside niche microenvironments that are completely unique as compared to those of the surrounding tissue, suggests that microenvironments exert a tremendous influence over stem cell behavior. Even mathematical models of hematopoiesis suggested that stem cell-extrinsic regulation was the best way to explain why stem cells responded to a wide variety of physiological needs (Loeffler and Roeder 2002; Roeder and Lorenz 2006). Experimentally, microenvironmental control of mammary progenitors, hematopoietic stem cells, embryonic stem cells, and neural progenitors has been shown by use of functional assays on arrayed combinatorial microenvironments (Flaim et al. 2005; Soen et al. 2006; LaBarge et al. 2009; Lutolf et al. 2009). And perhaps the grandest demonstration of the power of the microenvironment over stem cell function was shown repeatedly when adult stem cells from one tissue were shown to give rise to other tissues after they were placed in tissue-specific microenvironments different from their native ones (Blau et al. 2001; Boulanger et al. 2007; Booth et al. 2008). An important likelihood that arises from those experiments is that the phenotype of a stem cell is probably affected by its microenvironment (LaBarge et al. 2007). To completely understand the identity and control of mammary stem cells, we must meticulously define the microenvironment(s) they inhabit.As Petersen and Polyak point out, the methodology used to describe the stem cell hierarchy in adult hematopoietic systems has guided many subsequent studies aimed at identifying hierarchies in epithelial tissues. Accordingly, tissues are dissociated into suspensions of single cells, fractionated with a cell sorting technology, and the fractions are assayed for stem cell activity in a number of culture assays and in vivo when possible. Demonstration that a single cell can give rise to the tissue in question is often referred to as the “gold standard” experiment, and it is an unfortunate burden of proof held over from the hematopoietic field. Blood is an interesting tissue in that centers for hematopoiesis shift throughout development among locations that are anatomically close to the circulation, and it is thought that in adults, blood is produced from niches in marrow and vasculature (Sacchetti et al. 2007; Hooper et al. 2009; Butler et al. 2010). Thus, it makes sense that a single hematopoietic stem cell should regenerate the blood as nothing more is being asked of it than to do exactly what it was meant to, and to do it in the perfect microenvironment. Moreover, in the hematopoiesis model, where the microenvironment was essentially perfect, it stands to reason that one would only observe different activities according to the fraction from which single cells were derived. These facts may help explain why it has taken so long for acceptance of the idea that microenvironments can control stem cell activity. By comparison, adult mammary epithelial stem cells are distinct from the neonatal stem cells that made the initial mammary rudiment, and the adult stem cells evolved within an intricate epithelial architecture that was within a tissue stroma. That a single mouse mammary stem cell could give rise to an outgrowth was shown to occur at very low frequency (Shackleton et al. 2006; Stingl et al. 2006), and it has yet to be shown that a single normal human mammary stem cell can generate an outgrowth in a murine fat pad. Given the biological differences between blood and mammary epithelium, it is no surprise that the identity of human mammary stem cells and the mechanisms that govern them are still hotly debated.     

CSF-1 Receptor Signaling in Myeloid Cells

The CSF-1 receptor (CSF-1R) is activated by the homodimeric growth factors colony-stimulating factor-1 (CSF-1) and interleukin-34 (IL-34). It plays important roles in development and in innate immunity by regulating the development of most tissue macrophages and osteoclasts, of Langerhans cells of the skin, of Paneth cells of the small intestine, and of brain microglia. It also regulates the differentiation of neural progenitor cells and controls functions of oocytes and trophoblastic cells in the female reproductive tract. Owing to this broad tissue expression pattern, it plays a central role in neoplastic, inflammatory, and neurological diseases. In this review we summarize the evolution, structure, and regulation of expression of the CSF-1R gene. We review, the structures of CSF-1, IL-34, and the CSF-1R and the mechanism of ligand binding to and activation of the receptor. We further describe the pathways regulating macrophage survival, proliferation, differentiation, and chemotaxis downstream from the CSF-1R.The glycoprotein, colony-stimulating factor-1 (CSF-1), also known as macrophage-CSF (M-CSF), was the first of the CSFs to be purified (Stanley and Heard 1977) and was shown to stimulate the formation of colonies of macrophages (Stanley et al. 1978). This led to the identification (Guilbert and Stanley 1980) and purification (Yeung et al. 1987) of the CSF-1 receptor (CSF-1R) and the demonstration that it possessed intrinsic tyrosine kinase activity (Yeung et al. 1987). It was subsequently shown to be identical to the c-fms proto-oncoprotein (Sherr et al. 1985) previously studied by Sherr and colleagues (Rettenmier et al. 1985). The c-fms cDNA was cloned and shown to encode a typical class III receptor tyrosine kinase (RTK) (Coussens et al. 1986).The CSF-1R plays a central role in many diseases. Dominant inactivating mutations in the CSF-1R lead to adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (Rademakers et al. 2011; Nicholson et al. 2013). Inappropriate expression of the CSF-1R contributes to the development of leukemias and lymphomas, and autocrine and paracrine regulation of the CSF-1R enhances the progression and metastasis of solid tumors (reviewed in Pollard 2009; Chitu and Stanley 2014). In addition, regulation through the CSF-1R contributes to chronic inflammatory diseases (reviewed in Chitu and Stanley 2006; Chitu et al. 2012). This review focuses on the CSF-1R regulation and signaling in cells of the myeloid lineage.     

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.     

Metabolic Stress in Autophagy and Cell Death Pathways

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

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.     

On how mammary gland reprogramming metalloproteinases couple form with function

Metalloproteinases in extracellular proteolytic pathways are critical to mammary gland biology and tumorigenesis. However, intracellular and membrane proteases (e.g., caspases and cathepsins) may also play important roles.Khokha and Werb (2011) present a comprehensive overview of the roles of metalloproteinases in extracellular proteolytic pathways that are critical to mammary gland biology along with the deregulation of these enzymes that is associated with tumorigenesis. Indeed, many metalloproteinases have been confirmed to play causal roles in extracellular proteolysis. This has been shown for mammary gland development in knockout mice that lack these proteases and for mammary tumorigenesis by crossing metalloproteinase-null mice with transgenic mice predisposed to develop mammary tumors. The findings do not rule out causal roles for other proteases, however, including intracellular proteases. Such roles seem likely because there is functional redundancy among the >500 proteases in the human degradome and the >600 proteases in the murine degradome (Puente et al. 2003). Defining the role of any one protease is complex and there are examples of intracellular and membrane proteases that may, in addition to the metalloproteinases, contribute to mammary development and tumorigenesis.Khokha and Werb note that apoptosis, autophagy, and phagocytosis, all of which involve intracellular proteolysis, are critical to mammary gland biology. The primary mediators of the apoptotic cell death pathway are caspases, intracellular cysteine proteases that cleave after aspartic acid residues (Pop and Salvesen 2009). A variety of other intracellular proteases also have been implicated in apoptosis, including threonine proteases such as the proteasome (Dalton 2004); aspartic proteases such as cathepsin D (Conus and Simon 2008); serine proteases such as granzyme B (Kurschus et al. 2005); and cysteine cathepsins, such as cathepsins B and L (Vasiljeva and Turk 2008). In the case of the cysteine cathepsins, studies in a diverse array of cell lines indicate that they do not initiate apoptosis, but rather amplify caspase-dependent apoptosis (Droga-Mazovek et al. 2008; Oberle et al. 2010). Autophagy is an alternative cell death pathway that is central to both normal developmental processes and diseases, including cancer (for review, see Eskelinen and Saftig 2009). Essential in autophagy are autophagins, cysteine proteases involved in delipidation of other autophagic proteins and the development of autophagic vesicles (Marino et al. 2003), and lysosomal proteases that digest vesicle contents. An essential role for the lysosomal cysteine protease cathepsin L has been confirmed; in tissues of mice lacking this enzyme there is reduced autophagic degradation and an associated increase in large autophagolysosomes (Dennemarker et al. 2010). Phagocytosis is a form of endocytosis in which, like autophagy, lysosomal proteases degrade vesicle contents. For example, collagens can be degraded intracellularly by lysosomal proteases following uptake by the endocytic receptor urokinase plasminogen activator receptor-associated protein (uPARAP) or Endo180 (Kjoller et al. 2004). This intracellular degradation of collagens is linked to mammary tumorigenesis as the size of mouse mammary tumor virus (MMTV)-PyMT-induced mammary tumors is reduced in uPARAP-null mice (Curino et al. 2005).The studies on uPARAP show an indirect role for lysosomal proteases in mammary tumorigenesis, whereas other studies show a direct role for the lysosomal cysteine cathepsins. In cathepsin-B-null mice crossed with MMTV-PyMT mice, there is a reduction in high-grade invasive ductal carcinomas (Vasiljeva et al. 2008). The lysosomal cysteine protease cathepsin X (Z) becomes localized on the plasma membranes of the MMTV-PyMT mammary tumors in the cathepsin-B-null mice, compensating in part for an absence of cathepsin B on the tumor membrane (Sevenich et al. 2010). Cathepsin B is known to be present and active on the cell membrane in a wide variety of tumors, including mammary tumors (for review, see Mohamed and Sloane 2006). Further evidence that cathepsin X can compensate for loss of cathepsin B and vice versa comes from studies of MMTV-PyMT mammary tumors in mice lacking both enzymes. In these mice, synergistic delays in tumor development and reductions in the number and sizes of lung metastases are observed (Sevenich et al. 2010). The existence of such reciprocal compensatory mechanisms between two proteases indicates how difficult it is to define the function of any individual protease in a developmental or pathobiological process.In general, as indicated by Khokha and Werb, the metalloproteinases that play roles in mammary development also contribute to mammary tumorigenesis when they are deregulated. In contrast, although roles in tumorigenesis have been shown for other proteases, they have not been shown to play roles in mammary development. This absence of information may reflect the experimental design and focus of the investigator, the presence of a severe phenotype in tissues other than the mammary gland, and embryonic or perinatal lethality of mice lacking the protease. The membrane serine protease matriptase provides an illustrative example, as mice lacking it die shortly after birth owing to a defect in epidermal integrity (List et al. 2002). Matriptase is expressed at high levels in the terminal end buds of growing mammary ducts (Lee et al. 2010), which is consistent with a role for this enzyme in mammary development. As it is not possible to study mammary development in matriptase-null mice, Lee and colleagues used 3D cultures of mammary epithelial cells in basement membrane in which they decreased matriptase expression by RNA interference (RNAi) or matriptase activity by using a small molecule inhibitor. Activation of pro-HGF (hepatocyte growth factor) by matriptase resulted in the formation of acini with lumens, lobular, and ductal structures. Reduced expression or activity of matriptase abrogates these effects, consistent with matriptase-mediating mammary gland morphogenesis through HGF activation. In vitro models, even organotypic models, do not recapitulate all of the cell–cell interactions critical to development or tumorigenesis. Therefore, an alternative approach would be the use of tissue-specific and conditional knockouts to study the roles of proteases that cannot be studied in null mice owing to embryonic or perinatal lethality.Khokha and Werb describe protumorigenic roles for metalloproteinases; however, some metalloproteinases in addition to serine and cysteine proteases play antitumor or protective roles (for review, see Lopez-Otin and Matrisian 2007). MMP-8 was the first protease reported to play a tumor-suppressive role. MMP-8 reduces the incidence of skin tumors (Balbin et al. 2003) and breast cancer metastases (Decock et al. 2008; Gutierrez-Fernandez et al. 2008). Moreover, some proteases can be both anti- and protumorigenic. MMP-3 promotes side branching of mammary ducts during normal development and mammary tumors when an active form is expressed in the mammary glands of transgenic mice (Sternlicht et al. 1999), yet protects against chemically induced squamous cell carcinoma and mammary tumors (Lopez-Otin and Matrisian 2007). Although aspartic proteases had not previously been reported to be antitumorigenic, Yamamoto and colleagues (Kawakubo et al. 2008) found that the mammary glands of mice lacking cathepsin E, an intracellular endolysosomal aspartic protease, show a grossly abnormal morphology that is consistent with cathepsin-E-regulating mammary gland differentiation. The genes that are up-regulated (e.g., amphiregulin, IGFBP2, C-C, and C-X chemokine ligands) or down-regulated (e.g., antiapoptotic genes) in the mammary glands of the cathepsin-E-null mice are also associated with mammary gland tumorigenesis. Thus, cathepsin E is the first aspartic protease shown to play an antitumorigenic role in mammary tissue. The mechanisms by which the absence of cathepsin E exerts this effect are unknown. In this regard, Overall and colleagues are proponents of a systems biology approach (for review, see Rodriguez et al. 2010). They propose that we should not be analyzing protease-knockout mice in which a complex organism is responding over time to the absence of a single protease such as in the cathepsin E study. Instead, we need to use approaches such as high-content degradomics and bioinformatics to identify proteolytic networks and follow those with “specifically designed animal models for final validation.” This will be our challenge for the future.     

Biology of the TAM Receptors

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

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.