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.     

The Regulation of the p53-mediated Stress Response by MDM2 and MDM4

Exquisite control of the activity of p53 is necessary for mammalian survival. Too much p53 is lethal, whereas too little permits tumorigenesis. MDM2 and MDM4 are structurally related proteins critical for the control of p53 activity during development, homeostasis, and the response to stress. These two essential proteins regulate both the activation of p53 in response to stress and the recovery of cells following resolution of the damage, yet both are oncogenic when overexpressed. Thus, multiple regulatory circuits ensure that their activities are fine-tuned to promote tumor-free survival. Numerous diverse stressors activate p53, and much research has gone into trying to find commonalities between them that would explain the mechanism by which p53 becomes active. It is now clear that although these diverse stressors activate p53 by different biochemical pathways, one common feature is the effort they direct, through a variety of means, toward disrupting the functions of both MDM2 and MDM4. This article provides an overview of the relationship between MDM2 and MDM4, features the various biochemical mechanisms by which p53 is activated through inhibition of their functions, and proposes some emerging areas for investigation of the p53-mediated stress response.Regulation of the p53-mediated stress response by the essential inhibitory proteins MDM2 and MDM4 is critical for survival. In response to stressors such as ionizing radiation, p53 induces a number of potentially lethal but tumor-suppressive processes, including cell cycle arrest, senescence, and apoptosis (reviewed by Horn and Vousden 2007). Both MDM2 and MDM4 are critical to surviving the p53-mediated stress response to whole body ionizing irradiation as mice with reduced levels of either protein undergo p53-dependent death after exposure to doses of radiation that are sublethal to wild-type mice (Mendrysa et al. 2003; Terzian et al. 2007). MDM2 and MDM4 are also required to control p53 function during development, as shown by the early embryonic death of mice lacking either MDM2 or MDM4, unless they also lack p53 (Jones et al. 1995; Montes de Oca Luna et al. 1995; Parant et al. 2001; Migliorini et al. 2002).Although both MDM2 and MDM4 are essential for development, they are detrimental to long-term survival when in excess, because both are oncogenic. Both MDM2 and MDM4 confer the tumorigenic phenotype on cultured cells when experimentally overexpressed (Fakharzadeh et al. 1991; Danovi et al. 2004). In addition, targeted expression of MDM2 in the mammary gland results in tumorigenesis (Lundgren et al. 1997). In people, single nucleotide polymorphisms that reduce expression of either of the orthologs of MDM2 or MDM4 (also referred to as Hdm2 and Hdm4) correlate with increased risk for breast cancer (Bond et al. 2004; Atwal et al. 2009). Approximately 10% of human tumors have been found to overexpress either MDM2 or MDM4 and many of these express wild-type p53 (reviewed in Toledo and Wahl 2006). Because the majority of human cancers express mutant forms of p53, overexpression of MDM2 and MDM4 in the subset of tumors expressing wild-type p53 supports the notion that excessive MDM2 and MDM4 promote tumorigenesis, at least in part, by blocking p53 function. Thus, limiting the activities of MDM2 and MDM4 is important to prevent cancer.     

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.     

Mutant p53 Gain-of-Function in Cancer

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

Mitochondrial Evolution

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

Endocytosis,Signaling, and Beyond

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

Wnt Signaling from Development to Disease: Insights from Model Systems

One of the early surprises in the study of cell adhesion was the discovery that β-catenin plays dual roles, serving as an essential component of cadherin-based cell–cell adherens junctions and also serving as the key regulated effector of the Wnt signaling pathway. Here, we review our current model of Wnt signaling and discuss how recent work using model organisms has advanced our understanding of the roles Wnt signaling plays in both normal development and in disease. These data help flesh out the mechanisms of signaling from the membrane to the nucleus, revealing new protein players and providing novel information about known components of the pathway.Modern biomedical science is a partnership between scientists studying basic cell and developmental processes in model systems and clinicians exploring the basis of human disease. Few fields exemplify this better than Wnt signaling, born 22 years ago with the realization that the oncogene int1 and the Drosophila developmental patterning gene wingless (wg) are homologs (Cabrera et al. 1987; Rijsewijk et al. 1987). Additional connections further fueled research. Drosophila Armadillo (Arm), a component of the Wg pathway, is the homolog of the cell junction proteins β-catenin (βcat) and plakoglobin (McCrea et al. 1991; Peifer et al. 1992; Peifer and Wieschaus 1990) joining Wnt signaling and cadherin-based cell adhesion, a connection we still do not fully understand (see Heuberger and Birchmeier 2009). Adenomatous polyposis coli (APC), the tumor suppressor mutated in most colon cancers, binds βcat and is a key regulator of Wnt signaling (Rubinfeld et al. 1993; Su et al. 1993), putting the Wnt field even more squarely in the center of cancer research. Here, we outline recent advances in understanding Wnt signaling, casting new light on these critical regulators of development, homeostasis, and disease.     

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.     

Gap Junctions

Gap junctions are aggregates of intercellular channels that permit direct cell–cell transfer of ions and small molecules. Initially described as low-resistance ion pathways joining excitable cells (nerve and muscle), gap junctions are found joining virtually all cells in solid tissues. Their long evolutionary history has permitted adaptation of gap-junctional intercellular communication to a variety of functions, with multiple regulatory mechanisms. Gap-junctional channels are composed of hexamers of medium-sized families of integral proteins: connexins in chordates and innexins in precordates. The functions of gap junctions have been explored by studying mutations in flies, worms, and humans, and targeted gene disruption in mice. These studies have revealed a wide diversity of function in tissue and organ biology.Gap junctions are clusters of intercellular channels that allow direct diffusion of ions and small molecules between adjacent cells. The intercellular channels are formed by head-to-head docking of hexameric assemblies (connexons) of tetraspan integral membrane proteins, the connexins (Cx) (Goodenough et al. 1996). These channels cluster into polymorphic maculae or plaques containing a few to thousands of units (Fig. 1). The close membrane apposition required to allow the docking between connexons sterically excludes most other membrane proteins, leaving a narrow ∼2 nm extracellular “gap” for which the junction is named (Fig. 2). Gap junctions in prechordates are composed of innexins (Phelan et al. 1998; Phelan 2005). In chordates, connexins arose by convergent evolution (Alexopoulos et al. 2004), to expand by gene duplication (Cruciani and Mikalsen 2007) into a 21-member gene family. Three innexin-related proteins, called pannexins, have persisted in vertebrates, although it is not clear if they form intercellular channels (Panchin et al. 2000; Bruzzone et al. 2003). 7Å-resolution electron crystallographic structures of intercellular channels composed of either a carboxy-terminal truncation of Cx43 (Unger et al. 1999; Yeager and Harris 2007) or an M34A mutant of Cx26 (Oshima et al. 2007) are available. The overall pore morphologies are similar with the exception of a “plug” in the Cx26 channel pore. The density of this plug is substantively decreased by deletion of amino acids 2–7, suggesting that the amino-terminus contributes to this structure (Oshima et al. 2008). A 3.5-Å X-ray crystallographic structure has visualized the amino-terminus of Cx26 folded into the mouth of the channel without forming a plug, thought to be an image of the open channel conformation (Maeda et al. 2009). The amino-terminus has been physiologically implicated in voltage-gating of the Cx26 and Cx32 channels (Purnick et al. 2000; Oh et al. 2004), lending support to a role for the amino-terminus as a gating structure. However, Cx43 also shows voltage-gating, and its lack of any structure resembling a plug remains unresolved. A comparison of a 1985 intercellular channel structure (Makowski 1985) with the 2009 3.5Å structure (Maeda et al. 2009) summarizes a quarter-century of X-ray progress (Fig. 3).Open in a separate windowFigure 1.A diagram showing the multiple levels of gap junction structure. Individual connexins assemble intracellularly into hexamers, called connexons, which then traffic to the cell surface. There, they dock with connexons in an adjacent cell, assembling an axial channel spanning two plasma membranes and a narrow extracellular “gap.”Open in a separate windowFigure 2.Electron microscopy of gap junctions joining adjacent hepatocytes in the mouse. The gap junction (GJ) is seen as an area of close plasma membrane apposition, clearly distinct from the tight junction (TJ) joining these cells. (Inset A) A high magnification view of the gap junction revealing the 2–3 nm “gap” (white arrows) separating the plasma membranes. (Inset B) A freeze-fracture replica of a gap junction showing the characteristic particles on the protoplasmic (P) fracture face and pits on the ectoplasmic (E) fracture face. The particles and pits show considerable disorder in their packing with an average 9-nm center-to-center spacing.Open in a separate windowFigure 3.A comparison of axial sections through gap-junction structures deduced from X-ray diffraction. The 1985 data (Makowski 1985) were acquired from gap junctions isolated biochemically from mouse liver containing mixtures of Cx32 and Cx26. The intercellular channel (CHANNEL) is blocked at the two cytoplasmic surfaces by electron density at the channel mouths along the sixfold symmetry axis. The 2009 data (Maeda et al. 2009), acquired from three-dimensional crystals of recombinant Cx26, resolve this density at the channel opening as the amino-termini of the connexin proteins, the 2009 model possibly showing an open channel structure.Most cells express multiple connexins. These may co-oligomerize into the same (homomeric) or mixed (heteromeric) connexons, although only certain combinations are permitted (Falk et al. 1997; Segretain and Falk 2004). A connexon may dock with an identical connexon to form a homotypic intercellular channel or with a connexon containing different connexins to form a heterotypic channel (Dedek et al. 2006). Although only some assembly combinations are permitted (White et al. 1994), the number of possible different intercellular channels formed by this 21-member family is astonishingly large. This diversity has significance because intercellular channels composed of different connexins have different physiological properties, including single-channel conductances and multiple conductance states (Takens-Kwak and Jongsma 1992), as well as permeabilities to experimental tracers (Elfgang et al. 1995) and to biologically relevant permeants (Gaunt and Subak-Sharpe 1979; Veenstra et al. 1995; Bevans et al. 1998; Gong and Nicholson 2001; Goldberg et al. 2002; Ayad et al. 2006; Harris 2007).Opening of extrajunctional connexons in the plasma membrane, described as “hemichannel” activity, can be experimentally induced in a variety of cell types. Because first observations of hemichannel activity were in an oocyte expression system (Paul et al. 1991) and dissociated retinal horizontal cells (DeVries and Schwartz 1992), the possible functions of hemichannels composed of connexins and pannexins has enjoyed vigorous investigation (Goodenough and Paul 2003; Bennett et al. 2003; Locovei et al. 2006; Evans et al. 2006; Srinivas et al. 2007; Schenk et al. 2008; Thompson and MacVicar 2008; Anselmi et al. 2008; Goodenough and Paul 2003). Hemichannels have been implicated in various forms of paracrine signaling, for example in providing a pathway for extracellular release of ATP (Cotrina et al. 1998; Kang et al. 2008), glutamate (Ye et al. 2003), NAD⁺ (Bruzzone et al. 2000), and prostaglandins (Jiang and Cherian 2003).     

The Desmosome

Desmosomes are intercellular junctions that tether intermediate filaments to the plasma membrane. Desmogleins and desmocollins, members of the cadherin superfamily, mediate adhesion at desmosomes. Cytoplasmic components of the desmosome associate with the desmosomal cadherin tails through a series of protein interactions, which serve to recruit intermediate filaments to sites of desmosome assembly. These desmosomal plaque components include plakoglobin and the plakophilins, members of the armadillo gene family. Linkage to the cytoskeleton is mediated by the intermediate filament binding protein, desmoplakin, which associates with both plakoglobin and plakophilins. Although desmosomes are critical for maintaining stable cell–cell adhesion, emerging evidence indicates that they are also dynamic structures that contribute to cellular processes beyond that of cell adhesion. This article outlines the structure and function of the major desmosomal proteins, and explores the contributions of this protein complex to tissue architecture and morphogenesis.The desmosome is an adhesive intercellular junction that is crucial to tissues that experience mechanical stress, such as the myocardium, bladder, gastrointestinal mucosa, and skin (Getsios et al. 2004b; Holthofer et al. 2007). The desmosome was first observed in the spinous layer of epidermis by the Italian pathologist Giulio Bizzozero (1846–1901). Bizzozero''s observations of these small dense nodules, subsequently named “nodes of Bizzozero,” led him to the insightful interpretation of these structures as adhesive cell–cell contact points. The term desmosome was later coined by Josef Schaffer in 1920 and is derived from the Greek words “desmo,” meaning bond or fastening, and “soma,” meaning body (Wells 2005; Calkins and Setzer 2007). The introduction of electron microscopy yielded a series of advances by Porter, Odland, and Kelly in the 1950s and 1960s, which revealed desmosome organization at the ultrastructural level. These studies and others indicated that the desmosome can be divided into three morphologically identifiable zones: the extracellular core region (desmoglea), the outer dense plaque (ODP), and the inner dense plaque (IDP) (Fig. 1A) (Kowalczyk et al. 1994; Schmidt et al. 1994; Green and Jones 1996; North et al. 1999; Garrod and Chidgey 2008).Open in a separate windowFigure 1.A model for the structure of desmosomes. (A) Electron micrograph of a desmosome. (B) Schematic of desmosomal proteins and relative distance from the plasma membrane (PM). The desmosomal cadherins, the desmogleins and desmocollins, extend into extracellular core and outer dense plaque (ODP) to establish contact and adhere to neighboring cells in a Ca²⁺-dependent manner. The cadherin cytoplasmic tails associate linker proteins, plakoglobin (PG), the plakophilins (PKP), and desmoplakin (DP). DP binds to keratin intermediate filaments (KIF) within the inner dense plaque (IDP), serving to tether the intermediate filaments to the plasma membrane. (Adapted with permission from Kottke et al. 2006.)In the mid 1970s, Skerrow and Matoltsy (Skerrow and Matoltsy 1974a; Skerrow and Matoltsy 1974b) advanced the field by isolating desmosomes using biochemical approaches (Bass-Zubek and Green 2007).These landmark studies provided a foundation for the Franke and Steinberg laboratories to characterize the transmembrane glycoproteins and cytoplasmic plaque proteins that linked the structure to the intermediate filament cytoskeleton, and to develop immunological tools for localizing specific components (Franke et al. 1981; Kapprell et al. 1985; Steinberg et al. 1987). Collectively, these and other studies shaped our current view of how desmosomal components are organized.The transmembrane glycoproteins, termed desmogleins and desmocollins (Garrod and Chidgey 2008), represent separate subfamilies of the cadherin superfamily of calcium dependent adhesion molecules. The extracellular domains of the desmogleins and desmocollins mediate adhesion, whereas the cytoplasmic tails of these cadherins associate with the desmosomal plaque proteins. The outer dense plaque consists of the cytoplasmic tails of the desmosomal cadherins, which bind to members of the armadillo and plakin family of linker proteins (Kowalczyk et al. 1994; Getsios et al. 2004b; Garrod and Chidgey 2008). Plakoglobin, a member of the armadillo family, binds directly to the cytoplasmic tails of both the desmogleins and the desmocollins (Wahl et al. 1996; Witcher et al. 1996). Desmoplakin, a member of the plakin family, interacts with both plakoglobin and another subgroup of armadillo family proteins, the plakophilins (Cowin and Burke 1996). Finally, the interaction between desmoplakin and the keratin filaments forms the inner dense plaque, tethering the cytoskeletal network to the adhesion complex (Fig. 1B) (Kowalczyk et al. 1994; Getsios et al. 2004b; Garrod and Chidgey 2008).The following sections of this article describe the structural and functional characteristics of the major desmosomal proteins. In addition, we discuss differences in tissue expression patterns of desmosomal proteins and the role of desmosomes in human disease. A comprehensive review of additional proteins found to regulate or associate with desmosomes is provided elsewhere (Holthofer et al. 2007) and discussion of desmosome dynamics is provided in Green et al. 2009.     

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).     

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.     

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).