Morphogen Gradient Formation

How morphogen gradients are formed in target tissues is a key question for understanding the mechanisms of morphological patterning. Here, we review different mechanisms of morphogen gradient formation from theoretical and experimental points of view. First, a simple, comprehensive overview of the underlying biophysical principles of several mechanisms of gradient formation is provided. We then discuss the advantages and limitations of different experimental approaches to gradient formation analysis.How a multicellular organism develops from a single fertilized cell has fascinated people throughout history. By looking at chick embryos of different developmental stages, Aristotle first noted that development is characterized by growing complexity and organization of the embryo (Balme 2002). During the 19th century, two events were recognized as key in development: cell proliferation and differentiation. Driesch first noted that to form organisms with correct morphological pattern and size, these processes must be controlled at the level of the whole organism. When he separated two sea urchin blastomeres, they produced two half-sized blastula, showing that cells are potentially independent, but function together to form a whole organism (Driesch 1891, 1908). Morgan noted the polarity of organisms and that regeneration in worms occurs with different rates at different positions. This led him to postulate that regeneration phenomena are influenced by gradients of “formative substances” (Morgan 1901).The idea that organisms are patterned by gradients of form-providing substances was explored by Boveri and Hörstadius to explain the patterning of the sea urchin embryo (Boveri 1901; Hörstadius 1935). The discovery of the Spemann organizer, i.e., a group of dorsal cells that when grafted onto the opposite ventral pole of a host gastrula induce a secondary body axis (Spemann and Mangold 1924), suggested that morphogenesis results from the action of signals that are released from localized groups of cells (“organizing centers”) to induce the differentiation of the cells around them (De Robertis 2006). Child proposed that these patterning “signals” represent metabolic gradients (Child 1941), but the mechanisms of their formation, regulation, and translation into pattern remained elusive.In 1952, Turing showed that chemical substances, which he called morphogens (to convey the idea of “form producers”), could self-organize into spatial patterns, starting from homogenous distributions (Turing 1952). Turing’s reaction–diffusion model shows that two or more morphogens with slightly different diffusion properties that react by auto- and cross-catalyzing or inhibiting their production, can generate spatial patterns of morphogen concentration. The reaction–diffusion formalism was used to model regeneration in hydra (Turing 1952), pigmentation of fish (Kondo and Asai 1995; Kondo 2002), and snails (Meinhardt 2003).At the same time that Turing showed that pattern can self-organize from the production, diffusion, and reaction of morphogens in all cells, the idea that morphogens are released from localized sources (“organizers” à la Spemann) and form concentration gradients was still explored. This idea was formalized by Wolpert with the French flag model for generation of positional information (Wolpert 1969). According to this model, morphogen is secreted from a group of source cells and forms a gradient of concentration in the target tissue. Different target genes are expressed above distinct concentration thresholds, i.e., at different distances to the source, hence generating a spatial pattern of gene expression (Fig. 1C).Open in a separate windowFigure 1.Tissue geometry and simplifications. (A) Gradients in epithelia (left) and mesenchymal tissues (right). Because of symmetry considerations, one row of cells (red outline) is representative for the whole gradient. (B) Magnified view of the red row of cells shown in A. Cells with differently colored nuclei (brown, orange, and blue) express different target genes. (C) A continuum model in which individual cells are ignored and the concentration is a function of the positions x. The morphogen activates different target genes above different concentration thresholds (brown and orange).Experiments in the 1970s and later confirmed that tissues are patterned by morphogen gradients. Sander showed that a morphogen released from the posterior cytoplasm specifies anterioposterior position in the insect egg (Sander 1976). Chick wing bud development was explained by a morphogen gradient emanating from the zone of polarizing activity to specify digit positions (Saunders 1972; Tickle, et al. 1975; Tickle 1999). The most definitive example of a morphogen was provided with the identification of Bicoid function in the Drosophila embryo (Nüsslein-Volhard and Wieschaus 1980; Frohnhöfer and Nüsslein-Volhard 1986; Nüsslein-Volhard et al. 1987) and the visualization of its gradient by antibody staining (Driever and Nüsslein-Volhard 1988b, 1988a; reviewed in Ephrussi and St Johnston 2004). Since then, many examples of morphogen gradients acting in different organs and species have been found.In an attempt to understand pattern formation in more depth, quantitative models of gradient formation have been developed. An early model by Crick shows that freely diffusing morphogen produced in a source cell and destroyed in a “sink” cell at a distance would produce a linear gradient in developmentally relevant timescales (Crick 1970). Today, it is known that a localized “sink” is not necessary for gradient formation: Gradients can form if all cells act as sinks and degrade morphogen, or even if morphogen is not degraded at all. Here, we review different mechanisms of gradient formation, the properties of these gradients, and the implications for patterning. We discuss the theory behind these mechanisms and the supporting experimental data.     

Protein Targeting and Transport as a Necessary Consequence of Increased Cellular Complexity

With increasing intracellular complexity, a new cell-biological problem that is the allocation of cytoplasmically synthesized proteins to their final destinations within the cell emerged. A special challenge is thereby the translocation of proteins into or across cellular membranes. The underlying mechanisms are only in parts well understood, but it can be assumed that the course of cellular evolution had a deep impact on the design of the required molecular machines. In this article, we aim to summarize the current knowledge and concepts of the evolutionary development of protein trafficking as a necessary premise and consequence of increased cellular complexity.

The evolution of modern cells is arguably the most challenging and important problem the field of biology has ever faced …—Carl R. Woese(Woese 2002)

Current models may accept that all modern eukaryotic cells arose from a single common ancestor (the cenancestral eukaryote), the nature of which is—owing to the lack of direct living or fossil descendants—still highly under debate (de Duve 2007). The chimeric nature of eukaryotic genomes with eubacterial and archaebacterial shares led to a discussion about the origin of this first “proto-eukaryote.” Several models exist (see Fig. 1), which either place the evolution of the nucleus before or after the emergence of the mitochondrion (outlined in Koonin 2010; Martijn and Ettema 2013). According to the different postulated scenarios (summarized in Embley and Martin 2006), eukaryotes in the latter case might have evolved by endosymbiosis between a hydrogen-producing, oxygen-producing, or sulfur-dependent α-proteobacterium and an archaebacterial host (Fig. 1C). The resulting mitochondriate prokaryote would have evolved the nucleus subsequently. In other scenarios (Fig. 1B), the cenancestral eukaryote emerged by cellular fusion or endosymbiosis of a Gram-negative, maybe hydrogen-producing, eubacterium and a methanogenic archaebacterium or eocyte, leading to a primitive but nucleated amitochondrial (archezoan) cell (Embley and Martin 2006, and references therein). As a third alternative, Cavalier-Smith (2002) suggested a common eubacterial ancestor for eukaryotes and archaebacteria (the Neomuran hypothesis) (Fig. 1A).Open in a separate windowFigure 1.Evolution of the last common ancestor of all eukaryotic cells. A schematic depiction of the early eukaryogenesis. Because of the lack of living and fossil descendants, several opposing models are discussed (A–C). The anticipated order of events is shown as a flow chart. For details, see text. (Derived from Embley and Martin 2006; Koonin 2010.)     

The Structure and Function of Bacterial Actin Homologs

During the past decade, the appreciation and understanding of how bacterial cells can be organized in both space and time have been revolutionized by the identification and characterization of multiple bacterial homologs of the eukaryotic actin cytoskeleton. Some of these bacterial actins, such as the plasmid-borne ParM protein, have highly specialized functions, whereas other bacterial actins, such as the chromosomally encoded MreB protein, have been implicated in a wide array of cellular activities. In this review we cover our current understanding of the structure, assembly, function, and regulation of bacterial actins. We focus on ParM as a well-understood reductionist model and on MreB as a central organizer of multiple aspects of bacterial cell biology. We also discuss the outstanding puzzles in the field and possible directions where this fast-developing area may progress in the future.The discovery of cytoskeletal proteins in bacteria has fundamentally altered our understanding of the organization and evolution of bacteria as cells. Homologs of eukaryotic actin represent the most molecularly and functionally diverse family of bacterial cytoskeletal elements. Recent phylogenetic studies have identified more than 20 subgroups of bacterial actin homologs (Derman et al. 2009) (Fig. 1). Many of these bacterial actins are encoded on extrachromosomal plasmids, but most bacterial species with nonspherical morphologies also encode chromosomal actin homologs (Daniel and Errington 2003). The two earliest proteins to be characterized as bacterial actins were the chromosomal protein MreB (Jones et al. 2001) and the plasmidic protein ParM (Jensen and Gerdes 1997). MreB and ParM remain the best-characterized of the bacterial actins and we will thus focus on these two proteins for most of this article.Open in a separate windowFigure 1.The superfamily of bacterial actin homologs. Shown is a phylogenetic tree of the bacterial actin subfamilies that have been identified to date based on sequence homology. The subfamilies that have been experimentally shown to polymerize are labeled and colored. (Courtesy of Joe Pogliano, based on Derman et al. 2009.)The appreciation that bacteria possess actin homologs only occurred in the past decade. MreB was first identified as a protein involved in cell shape regulation in Escherichia coli in the late 1980s (Doi et al. 1988). In the early 1990s, pioneering bioinformatic studies identified similarities in a group of ATPases that have five conserved motifs (Bork et al. 1992), a feature dubbed the actin superfamily fold. Although this group includes actin and MreB, it also contains proteins that do not polymerize into filaments, such as sugar kinases like hexokinase and chaperones like Hsp70. A number of bacterial proteins are present in the actin superfamily, including the bacterial cell division protein FtsA which interacts with the tubulin homolog FtsZ and may or may not form filaments in different contexts (van den Ent and Lowe 2000). Because MreB did not appear significantly more related to actin than these nonfilamentous proteins, the weak sequence similarity with actin was largely ignored for the better part of a decade. This changed in 2001 when two seminal papers showed that Bacillus subtilis MreB forms cytoskeletal filaments in vivo (Jones et al. 2001) and that Thermotoga maritima MreB forms cytoskeletal filaments in vitro (van den Ent et al. 2001). Indeed, structural and biochemical studies of both MreB and ParM have convincingly showed that these proteins closely resemble actin and polymerize into linear filaments in a nucleotide-dependent manner (Fig. 2).Open in a separate windowFigure 2.Structures of F-actin (Holmes et al. 1990), MreB (van den Ent et al. 2001), and ParM (van den Ent et al. 2002). (Left) Structures of F-actin filaments (PDB entry 1YAG). (Second from the left) MreB filaments from T. maritima (PDB entry 1JCE). (Center) ParM:ADP monomer in the “closed” conformation. (Second from the right) apo ParM monomer in the “open” conformation. (Right) ParM filament. Shown are the position of the nucleotide within the interdomain cleft, the conservation of fold, and the axis of the protofilament extension (arrow). Note that the conformational change shown for ParM from the “open” to “closed” state is predicted for all actin homologs. (Adapted, with permission from, Michie and Löwe 2006.)Research following the identification of bacterial cytoskeletal proteins has focused on understanding their assembly, regulation, and function. Here, we will summarize our current understanding of these issues and highlight the outstanding questions. We will begin with ParM, whose well-characterized assembly and dynamics represent a model for future studies of all cytoskeletal proteins. We will then focus on MreB, whose diverse activities appear to be central to the cell biology of many bacterial species.     

The Role of Functional Prion-Like Proteins in the Persistence of Memory

Prions are a self-templating amyloidogenic state of normal cellular proteins, such as prion protein (PrP). They have been identified as the pathogenic agents, contributing to a number of diseases of the nervous system. However, the discovery that the neuronal RNA-binding protein, cytoplasmic polyadenylation element-binding protein (CPEB), has a prion-like state that is involved in the stabilization of memory raised the possibility that prion-like proteins can serve normal physiological functions in the nervous system. Here, we review recent experimental evidence of prion-like properties of neuronal CPEB in various organisms and propose a model of how the prion-like state may stabilize memory.Prions are proteinaceous infectious agents that were discovered in the 1980s by Stanley Prusiner while studying Creutzfeldt–Jakob disease (Prusiner 1982). Prusiner and colleagues showed them to be an amyloidogenic, self-perpetuating, forms of a normal cellular protein, termed prion protein or PrP. Prp in its self-perpetuating state kills cells. Prusiner and colleagues found that PrPs exist in at least two conformations: monomeric and aggregated (Fig. 1). The transition among these forms occurs spontaneously and only the aggregated conformation is pathogenic. Soon, PrPs were found to contribute to other neurodegenerative disorders in people, including kuru, transmissible spongiform encephalopathies, as well as bovine spongiform encephalopathy in cows (Prusiner 1994; Aguzzi and Weissmann 1998).Open in a separate windowFigure 1.Pathogenic prions exist in two states (soluble and aggregated and self-perpetuating). The conversion from the soluble to the aggregated form is spontaneous and the aggregated, self-perpetuating form is often toxic and kills the cell.There is now a growing consensus that similar prion-like, self-templating mechanisms underlie a variety of neurodegenerative disorders, including amyotrophic lateral sclerosis, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease (Polymenidou and Cleveland 2012).Not all prions, however, appear to be disease causing. Fungal prions, for instance, are nontoxic, and some may even be beneficial to the cells that harbor them (Wickner 1994; Shorter and Lindquist 2005; Crow and Li 2011). In 2003, Si and Kandel serendipitously discovered a prion-like protein in multicellular eukaryotes—the nervous system of the marine snail Aplysia—whose aggregated and self-perpetuating form contributes to the maintenance of long-term changes in synaptic efficacy. This functional prion-like protein differs from pathogenic prions in two important ways: (1) The conversion to the prion-like state is regulated by a physiological signal, and (2) the aggregated form has an identified physiological function (Fig. 2). Recent identification of new functional prion-like proteins in various organisms, including human, supports the idea that nonpathogenic prions may perform a wide range of biologically meaningful roles (Coustou et al. 1997; Eaglestone et al. 1999; True and Lindquist 2000; Ishimaru et al. 2003; True et al. 2004; Hou et al. 2011; Jarosz et al. 2014).Open in a separate windowFigure 2.“Functional” prion: memory. “Functional” prions differ from conventional prions in two ways. First, the conversion is triggered by a physiological signal, and second, the aggregated, self-perpetrating forms have a physiological function. 5-HT, Serotonin; DA, dopamine.In this review, we focus on functional prion-like proteins in the brain and specifically on the prion-like properties of the cytoplasmic polyadenylation element-binding protein (CPEB), and examine how the prion-like state can control protein synthesis at the synapse and, thereby, synaptic plasticity and long-lasting memory. We anticipate the studies of CPEB would also provide some generalizable concepts as to how prion-based protein switches in multicellular eukaryotes may work.     

The Structure and Function of the Eukaryotic Ribosome

Structures of the bacterial ribosome have provided a framework for understanding universal mechanisms of protein synthesis. However, the eukaryotic ribosome is much larger than it is in bacteria, and its activity is fundamentally different in many key ways. Recent cryo-electron microscopy reconstructions and X-ray crystal structures of eukaryotic ribosomes and ribosomal subunits now provide an unprecedented opportunity to explore mechanisms of eukaryotic translation and its regulation in atomic detail. This review describes the X-ray crystal structures of the Tetrahymena thermophila 40S and 60S subunits and the Saccharomyces cerevisiae 80S ribosome, as well as cryo-electron microscopy reconstructions of translating yeast and plant 80S ribosomes. Mechanistic questions about translation in eukaryotes that will require additional structural insights to be resolved are also presented.All ribosomes are composed of two subunits, both of which are built from RNA and protein (Figs. ​(Figs.11 and ​and2).2). Bacterial ribosomes, for example of Escherichia coli, contain a small subunit (SSU) composed of one 16S ribosomal RNA (rRNA) and 21 ribosomal proteins (r-proteins) (Figs. ​(Figs.1A1A and ​and1B)1B) and a large subunit (LSU) containing 5S and 23S rRNAs and 33 r-proteins (Fig. 2A). Crystal structures of prokaryotic ribosomal particles, namely, the Thermus thermophilus SSU (Schluenzen et al. 2000; Wimberly et al. 2000), Haloarcula marismortui and Deinococcus radiodurans LSU (Ban et al. 2000; Harms et al. 2001), and E. coli and T. thermophilus 70S ribosomes (Yusupov et al. 2001; Schuwirth et al. 2005; Selmer et al. 2006), reveal the complex architecture that derives from the network of interactions connecting the individual r-proteins with each other and with the rRNAs (Brodersen et al. 2002; Klein et al. 2004). The 16S rRNA can be divided into four domains, which together with the r-proteins constitute the structural landmarks of the SSU (Wimberly et al. 2000) (Fig. 1A): The 5′ and 3′ minor (h44) domains with proteins S4, S5, S12, S16, S17, and S20 constitute the body (and spur or foot) of the SSU; the 3′ major domain forms the head, which is protein rich, containing S2, S3, S7, S9, S10, S13, S14, and S19; whereas the central domain makes up the platform by interacting with proteins S1, S6, S8, S11, S15, and S18 (Fig. 1B). The rRNA of the LSU can be divided into seven domains (including the 5S rRNA as domain VII), which—in contrast to the SSU—are intricately interwoven with the r-proteins as well as each other (Ban et al. 2000; Brodersen et al. 2002) (Fig. 2A). Structural landmarks on the LSU include the central protuberance (CP) and the flexible L1 and L7/L12 stalks (Fig. 2A).Open in a separate windowFigure 1.The bacterial and eukaryotic small ribosomal subunit. (A,B) Interface (upper) and solvent (lower) views of the bacterial 30S subunit (Jenner et al. 2010a). (A) 16S rRNA domains and associated r-proteins colored distinctly: b, body (blue); h, head (red); pt, platform (green); and h44, helix 44 (yellow). (B) 16S rRNA colored gray and r-proteins colored distinctly and labeled. (C–E) Interface and solvent views of the eukaryotic 40S subunit (Rabl et al. 2011), with (C) eukaryotic-specific r-proteins (red) and rRNA (pink) shown relative to conserved rRNA (gray) and r-proteins (blue), and with (D,E) 18S rRNA colored gray and r-proteins colored distinctly and labeled.Open in a separate windowFigure 2.The bacterial and eukaryotic large ribosomal subunit. (A) Interface (upper) and solvent (lower) views of the bacterial 50S subunit (Jenner et al. 2010b), with 23S rRNA domains and bacterial-specific (light blue) and conserved (blue) r-proteins colored distinctly: cp, central protuberance; L1, L1 stalk; and St, L7/L12 stalk (or P-stalk in archeaa/eukaryotes). (B–E) Interface and solvent views of the eukaryotic 60S subunit (Klinge et al. 2011), with (B) eukaryotic-specific r-proteins (red) and rRNA (pink) shown relative to conserved rRNA (gray) and r-proteins (blue), (C) eukaryotic-specific expansion segments (ES) colored distinctly, and (D,E) 28S rRNA colored gray and r-proteins colored distinctly and labeled.In contrast to their bacterial counterparts, eukaryotic ribosomes are much larger and more complex, containing additional rRNA in the form of so-called expansion segments (ES) as well as many additional r-proteins and r-protein extensions (Figs. 1C–E and ​and2C–E).2C–E). Compared with the ∼4500 nucleotides of rRNA and 54 r-proteins of the bacterial 70S ribosome, eukaryotic 80S ribosomes contain >5500 nucleotides of rRNA (SSU, 18S rRNA; LSU, 5S, 5.8S, and 25S rRNA) and 80 (79 in yeast) r-proteins. The first structural models for the eukaryotic (yeast) ribosome were built using 15-Å cryo–electon microscopy (cryo-EM) maps fitted with structures of the bacterial SSU (Wimberly et al. 2000) and archaeal LSU (Ban et al. 2000), thus identifying the location of a total of 46 eukaryotic r-proteins with bacterial and/or archaeal homologs as well as many ES (Spahn et al. 2001a). Subsequent cryo-EM reconstructions led to the localization of additional eukaryotic r-proteins, RACK1 (Sengupta et al. 2004) and S19e (Taylor et al. 2009) on the SSU and L30e (Halic et al. 2005) on the LSU, as well as more complete models of the rRNA derived from cryo-EM maps of canine and fungal 80S ribosomes at ∼9 Å (Chandramouli et al. 2008; Taylor et al. 2009). Recent cryo-EM reconstructions of plant and yeast 80S translating ribosomes at 5.5–6.1 Å enabled the correct placement of an additional six and 10 r-proteins on the SSU and LSU, respectively, as well as the tracing of many eukaryotic-specific r-protein extensions (Armache et al. 2010a,b). The full assignment of the r-proteins in the yeast and fungal 80S ribosomes, however, only became possible with the improved resolution (3.0–3.9 Å) resulting from the crystal structures of the SSU and LSU from Tetrahymena thermophila (Klinge et al. 2011; Rabl et al. 2011) and the Saccharomyces cerevisiae 80S ribosome (Figs. ​(Figs.1D,E1D,E and ​and2D,E)2D,E) (Ben-Shem et al. 2011).     

Chromosome Dynamics during Mitosis

The primary goal of mitosis is to partition duplicated chromosomes into daughter cells. Eukaryotic chromosomes are equipped with two distinct classes of intrinsic machineries, cohesin and condensins, that ensure their faithful segregation during mitosis. Cohesin holds sister chromatids together immediately after their synthesis during S phase until the establishment of bipolar attachments to the mitotic spindle in metaphase. Condensins, on the other hand, attempt to “resolve” sister chromatids by counteracting cohesin. The products of the balancing acts of cohesin and condensins are metaphase chromosomes, in which two rod-shaped chromatids are connected primarily at the centromere. In anaphase, this connection is released by the action of separase that proteolytically cleaves the remaining population of cohesin. Recent studies uncover how this series of events might be mechanistically coupled with each other and intricately regulated by a number of regulatory factors.In eukaryotic cells, genomic DNA is packaged into chromatin and stored in the cell nucleus, in which essential chromosomal processes, including DNA replication and gene expression, take place (Fig. 1, interphase). At the onset of mitosis, the nuclear envelope breaks down and chromatin is progressively converted into a discrete set of rod-shaped structures known as metaphase chromosomes (Fig. 1, metaphase). In each chromosome, a pair of sister kinetochores assembles at its centromeric region, and their bioriented attachment to the mitotic spindle acts as a prerequisite for equal segregation of sister chromatids. The linkage between sister chromatids is dissolved at the onset of anaphase, allowing them to be pulled apart to opposite poles of the cell (Fig. 1, anaphase). At the end of mitosis, the nuclear envelope reassembles around two sets of segregated chromatids, leading to the production of genetically identical daughter cells (Fig. 1, telophase).Open in a separate windowFigure 1.Overview of chromosome dynamics during mitosis. In addition to the crucial role of kinetochore–spindle interactions, an intricate balance between cohesive and resolving forces acting on sister chromatid arms (top left, inset) underlies the process of chromosome segregation. See the text for major events in chromosome segregation.Although the centromere–kinetochore region plays a crucial role in the segregation process, sister chromatid arms also undergo dynamic structural changes to facilitate their own separation. Conceptually, such structural changes are an outcome of two balancing forces, namely, cohesive and resolving forces (Fig. 1, top left, inset). The cohesive force holds a pair of duplicated arms until proper timing of separation, otherwise daughter cells would receive too many or too few copies of chromosomes. The resolving force, on the other hand, counteracts the cohesive force, reorganizing each chromosome into a pair of rod-shaped chromatids. From this standpoint, the pathway of chromosome segregation is regarded as a dynamic process, in which the initially robust cohesive force is gradually weakened and eventually dominated by the resolving force. Almost two decades ago, genetic and biochemical studies for the behavior of mitotic chromosomes converged productively, culminating in the discovery of cohesin (Guacci et al. 1997; Michaelis et al. 1997; Losada et al. 1998) and condensin (Hirano et al. 1997; Sutani et al. 1999), which are responsible for the cohesive and resolving forces, respectively. The subsequent characterizations of these two protein complexes have not only transformed our molecular understanding of chromosome dynamics during mitosis and meiosis, but also provided far-reaching implications in genome stability, as well as unexpected links to human diseases. In this article, I summarize recent progress in our understanding of mitotic chromosome dynamics with a major focus on the regulatory networks surrounding cohesin and condensin. I also discuss emerging topics and attempt to clarify outstanding questions in the field.     

Holliday Junction Resolvases

Four-way DNA intermediates, called Holliday junctions (HJs), can form during meiotic and mitotic recombination, and their removal is crucial for chromosome segregation. A group of ubiquitous and highly specialized structure-selective endonucleases catalyze the cleavage of HJs into two disconnected DNA duplexes in a reaction called HJ resolution. These enzymes, called HJ resolvases, have been identified in bacteria and their bacteriophages, archaea, and eukaryotes. In this review, we discuss fundamental aspects of the HJ structure and their interaction with junction-resolving enzymes. This is followed by a brief discussion of the eubacterial RuvABC enzymes, which provide the paradigm for HJ resolvases in other organisms. Finally, we review the biochemical and structural properties of some well-characterized resolvases from archaea, bacteriophage, and eukaryotes.Homologous recombination (HR) is an essential process that promotes genetic diversity during meiosis (see Lam and Keeney 2014; Zickler and Kleckner 2014). However, in somatic cells, HR plays a key role in conserving genetic information by facilitating DNA repair, thereby ensuring faithful genome duplication and limiting the divergence of repetitive DNA sequences (see Mehta and Haber 2014). As shown in Figure 1, HR is initiated by a DNA double-strand break, the ends of which are resected to produce single-stranded (ss) 3′-overhangs (see Symington 2014). Homologous strand invasion by one of the 3′ overhangs (e.g., one catalyzed by Escherichia coli RecA or human RAD51) leads to the formation of a displacement loop (D-loop) (see Morrical 2014). The invading 3′ end of the D-loop can then be extended by a DNA polymerase, which uses the homologous strand as a template for DNA synthesis. Recombination then proceeds in one of several different ways, some of which involve second-end capture, such that the other resected 3′ end anneals to the displaced strand of the D-loop (Szostak et al. 1983). In the resulting recombination intermediate, the two interacting DNAs are linked by nicked Holliday junctions (HJs). Additional DNA synthesis and nick ligation lead to the formation of a double Holliday junction (dHJ) intermediate. In eukaryotes, dHJs are removed primarily by “dissolution” (Fig. 1, bottom left) (see Bizard and Hickson 2014). This pathway involves the combined activities of a DNA helicase and a type IA topoisomerase, which catalyze branch migration and decatenation of the dHJ into noncrossover products (Manthei and Keck 2014). In somatic cells, this is essential for the avoidance of sister-chromatid exchanges (SCEs) and loss of heterozygosity. Alternatively, dHJs can be processed by “resolution” in reactions mediated by canonical or noncanonical mechanisms of endonuclease-mediated cleavage into either crossover or noncrossover products (Fig. 1, bottom middle and right).Open in a separate windowFigure 1.Pathways for the formation and processing of Holliday junctions. Resected DNA double-strand breaks invade homologous duplex DNA to create a joint molecule, or displacement-loop structure. The invading 3′ end then serves as a primer for DNA synthesis, leading to second end capture and the formation of a double Holliday junction. In eukaryotes, these structures are removed by “dissolution” (bottom left panel) or “resolution” (bottom middle and right panels). Canonical Holliday junction resolvases introduce a pair of symmetrical and coordinated nicks across one of the helical axes (bottom middle panel) to generate nicked DNA duplexes that can be directly ligated. Alternatively, noncanonical resolvases cleave Holliday junctions with asymmetric nicks to produce gapped and flapped DNA duplexes that require further processing prior to ligation (bottom right panel). *Mitochondrial Holliday junction resolvase.     

Widely Conserved Signaling Pathways in the Establishment of Cell Polarity

How are the asymmetric distributions of proteins, lipids, and RNAs established and maintained in various cell types? Studies from diverse organisms show that Par proteins, GTPases, kinases, and phosphoinositides participate in conserved signaling pathways to establish and maintain cell polarity.The asymmetric distribution of proteins, lipids, and RNAs is necessary for cell fate determination, differentiation, and specialized cell functions that underlie morphogenesis (St Johnston 2005; Gonczy 2008; Knoblich 2008; Macara and Mili 2008; Martin-Belmonte and Mostov 2008). A fundamental question is how this asymmetric distribution is established and maintained in different types of cells and tissues. The formation of a specialized apical surface on an epithelial cell seems quite different from the specification of axons versus dendrites in a neuron, or the asymmetric division of a nematode zygote. Yet, remarkably, a conserved molecular toolbox is used throughout the metazoa to establish and maintain cell polarity in these and many other contexts. This toolbox consists of proteins that are components of signal transduction pathways (Goldstein and Macara 2007; Assemat et al. 2008; Yamanaka and Ohno 2008). However, our understanding of these pathways, and their intersection with other signaling networks, remains incomplete. Moreover, the regulation and cross talk between the polarity proteins and other signaling components varies from one context to another, which complicates the task of dissecting polarity protein function. Nonetheless, rapid progress is being made in our understanding of polarity signaling, which is outlined in this article, with an emphasis on the Par proteins, because these proteins play major roles integrating diverse signals that regulate cell polarity (Fig. 1) (see Munro and Bowerman 2009; Prehoda 2009; Nelson 2009).Open in a separate windowFigure 1.An overview of Par complex signaling, showing inputs (bottom) and outputs (top) with cellular functions that are targeted by these pathways (italics).     

How Genes Have Illuminated the History of Early Americans and Latino Americans

The American continent currently accounts for ∼15% of the world population. Although first settled thousands of years ago and fitting its label as “the New World,” the European colonial expansion initiated in the late 15th century resulted in people from virtually every corner of the globe subsequently settling in the Americas. The arrival of large numbers of immigrants led to a dramatic decline of the Native American population and extensive population mixing. A salient feature of the current human population of the Americas is, thus, its great diversity. The genetic variation of the Native peoples that recent immigrants encountered had been shaped by demographic events acting since the initial peopling of the continent. Similarly, but on a compressed timescale, the colonial history of the Americas has had a major impact on the genetic makeup of the current population of the continent. A range of genetic analyses has been used to study both the ancient settlement of the continent and more recent history of population mixing. Here, I show how these two strands of research overlap and make use of results from other scientific disciplines to produce a fuller picture of the settlement of the continent at different time periods. The biological diversity of the Americas also provides prominent examples of the complex interaction between biological and social factors in constructing human identities and of the difficulties in defining human populations.A multiplicity of research approaches have been used to explore the original settlement of the American continent, often focusing on three prominent questions: (1) the route of entry of the initial settlers, (2) their time of arrival, and (3) the pattern of subsequent migration. These questions have been approached with variable degrees of success using various types of genetic markers examined in “Native” populations, defined on anthropological grounds (particularly language). Early studies used information from blood groups and proteins (Cavalli-Sforza et al. 1994) and were followed by DNA analyses mainly of mitochondrial DNA (mtDNA) (Forster et al. 1996; Tamm et al. 2007; Fagundes et al. 2008; Kitchen et al. 2008) and the Y chromosome (Lell et al. 1997; Bianchi et al. 1998; Karafet et al. 1999; Bortolini et al. 2003). The more recent studies have examined the human genome at increasing levels of resolution, from analyses with restricted sets of markers (Wang et al. 2007; Ray et al. 2010) to ongoing studies based on full genome sequences. Although a range of scenarios for the initial peopling of the Americas have been envisaged, genetic evidence points to the continent being settled by people migrating into the northwestern tip of the continent from Asia. This migration would have been facilitated by the existence, at that time, of a land bridge connecting Siberia to Alaska, which later was submerged beneath the Bering Strait by the rising sea level at the end of the last glaciation, around 15,000 years ago (Fiedel 2000). Genetic support for an American settlement from Eastern Siberia includes the finding that Native Americans are genetically most similar to North Asians (Cavalli-Sforza et al. 1994; Wang et al. 2007) and the existence of a gradient of declining genetic diversity from northwest North America southward (Wang et al. 2007; Reich et al. 2012). This gradient extends beyond that seen in the “Old World” for populations at increasing distance from Africa, possibly resulting from a sequence of population contractions that occurred as small groups of humans moved from settled areas into uninhabited territories (Ramachandran et al. 2005; Handley et al. 2007; Wang et al. 2007). The American continent, being the last major landmass to have been settled by humans, shows a low genetic diversity as compared with all other continents (Wang et al. 2007).Estimating the date of the initial settlement of the Americas has proven a difficult and contentious issue. Geological information provides a key reference point in that because of extensive ice sheets covering North America at the peak of the last glaciation (around 20,000 years ago), the continent would have been impenetrable then (Fig. 1). Therefore, this leaves two broad opportunities for settlement: before or after this last glacial maximum (LGM). Calculating the time of initial settlement of the continent from genetic information requires a number of assumptions of which the exact validity is difficult to assess, including variation in factors such as population demography, mutation rates, and the influence of selection. Perhaps, not surprisingly, the range of genetic estimates for the time of human settlement of America is quite wide, extending to both sides of the glacial maximum. It is, however, encouraging that most of the recent estimates, based on increasingly larger amounts of data and more sophisticated statistical methods, point to a settlement not long after the LGM. These estimates show greater consistency with the archaeological evidence, which, although itself not devoid of controversy, points to a human presence in the Americas by ∼14,000 years ago.Open in a separate windowFigure 1.First peopling of the American continent. Settlement is thought to have occurred from Eastern Siberia through several waves of migration (arrows) across a land bridge connecting Siberia to Alaska, existing at the time. Crossing was impossible during the last glacial maximum (LGM) (∼20,000 years ago) because of glaciers covering a large part of North America. Most genetic studies of contemporary Native Americans point to a settlement of the continents soon after the LGM, subsequent to the retreat of the ice sheets. Although classical studies associated initial settlement with the Clovis archaeological complex of North America (∼13,000 years ago), older sites have been identified, including Monte Verde in South America (dated at ∼15,000 years ago). The Native American populations placed on this map are those included in the phylogenetic tree shown in Figure 3. Analysis of genetic data from these populations is consistent with the important role of the coast during the initial settlement of the continent (Reich et al. 2012).The pattern of migration into the continent has also been the subject of considerable disagreement. An influential model put forward in the mid-1980s posited that the settlement of the continent occurred in three sequential migratory waves from Asia, corresponding to the three major linguistic stocks in which the linguist Joseph Greenberg classified Native American languages (Greenberg et al. 1986; Greenberg 1987; Ruhlen 1991). The first migration would have given rise to a very large Amerind linguistic family comprising populations living all over the continent, whereas two subsequent migrations, restricted to North America and the Arctic, would be associated with populations speaking languages of the Na-Dene and Eskimo-Aleut linguistic families, respectively. Although early blood group and protein data were interpreted in support of the Greenberg model (Cavalli-Sforza et al. 1994), subsequent mtDNA and Y-chromosome analyses have been mostly interpreted as indicative of a single migration wave into the continent (Bonatto and Salzano 1997; Tamm et al. 2007; Fagundes et al. 2008; Kitchen et al. 2008). The recent genome-wide surveys of diversity with increasing resolution have, however, provided a different view. These are inconsistent with the single migration model and are more in line with the occurrence of multiple migrations (Fig. 1). Particularly strong support for several ancient migrations comes from a study based on a large survey of populations and using data for hundreds of thousands of genetic markers. With this type of data, it is possible to estimate the ancestry of every segment of DNA along the genome and state whether such a segment is of African, European, or Native American origin. Analyses can then focus only on the Native American segments of the genome (Fig. 2). This means that Native American individuals, and populations, that previously had to be excluded from study because of admixture with non-Natives can now be included, facilitating a more extensive population survey and reducing bias. These recent data have provided strong evidence that the Eskimo-Aleut, Na-Dene, and Amerind linguistic groups show evidence of differential gene flow from Asia, inconsistent with stemming from a discrete single colonization event with no subsequent migration (Fig. 1). Noticeably, although North American populations show evidence of multiple episodes of gene exchange with Asia, Native populations from Mexico to the Southern tip of South America appear to stem from one colonization wave with no subsequent Asian gene flow. This observation agrees with the highly controversial proposal of grouping widely separated Native American languages into a single “Amerindian” linguistic family (Greenberg 1987; Ruhlen 1991). These data also confirm the correlation of population diversity with distance from the Bering Strait, in agreement with settlement in a north-to-south direction. Interestingly, this correlation increases when considering the coasts as facilitators of population movement, suggesting an important role of the coast during the initial population dispersals on the continent. A phylogenetic tree relating the Native American populations examined in that survey is also consistent with the north-to-south settlement of the continent, as it shows a sequence of major population splits separating groups of populations mostly along a north-to-south axis (Figs. 1 and ​and3).3). Consistent with some degree of parallel evolution for languages and genes (Cavalli-Sforza et al. 1994), resulting from population separation followed by relative isolation, the major clusters of populations in this genetic tree show a broad correspondence with the linguistic affiliation of the populations (Fig. 3).Open in a separate windowFigure 2.Inference of local ancestry along the two copies of chromosome 1 in an admixed Native American individual. The height of the thick line indicates local ancestry as the number of chromosome copies at that position that are estimated to be Native American (0, 1, or 2). Numbers on the x-axis refer to the position along chromosome 1 (in kilobases) of the genetic markers allowing inference of local ancestry. (Modified from data in Reich et al. 2012.)Open in a separate windowFigure 3.Phylogenetic tree relating representative African, European, Oceanian, East Asian, and Native American populations based on high-density genetic marker data. For this analysis, Native American data used was restricted to genome segments of confirmed Native ancestry (determined as in Fig. 2). The tree branches are color-coded to represent the linguistic affiliation of the populations, as shown in the inset. Numbers in parentheses refer to sample size in each population. The length of the branches on this tree is proportional to a measure of genetic differentiation (F_ST). (From Reich et al. 2012; reprinted, with permission, from the author.)The recent study by Reich et al. (2012) illustrates the potential of high-density genotyping for extending studies focused on the original settlement of the Americas to Native individuals with evidence of admixture with recent immigrants. This admixture is extensive across the continent and involves not only Natives but also the general population, particularly in the countries of what is now referred to as Latin America. Historically, a major driver behind population mixing in this region was the fact that immigrants from Spain and Portugal, particularly in the early phases of the colonial expansion, were mostly men (Boyd-Bowman 1973). It is well documented that many Conquistadors had children with Native women, the most famous example possibly being that of the Conquistador of Mexico, Hernán Cortez, and the Nahua woman known as “Malinche” (Fig. 4). This “sex-biased” pattern of mating between immigrant men and Native women had been alluded to by historians (Morner 1967), but it was only with mtDNA and Y-chromosome studies that the full genetic impact of this feature became apparent. Because mtDNA and the Y chromosome are only transmitted by mothers and fathers, respectively, they allow the inference of the maternal (mtDNA) and paternal (Y-chromosome) ancestry of individuals. One of the first such studies was performed in Antioquia (Colombia), a population traditionally considered as mainly of Spanish descent. Consistent with this view, it was found that >90% of men in Antioquia had Y-chromosome lineages of European origin (Carvajal-Carmona et al. 2000). Surprisingly, when examining their mtDNA, a sharply different picture was observed. In 90% of individuals, maternal ancestry was Native American (Carvajal-Carmona et al. 2000). Similar observations have now been made in many Latin American countries (Alves-Silva et al. 2000; Green et al. 2000; Carvalho-Silva et al. 2001; Marrero et al. 2007), although with a considerable variation in ancestry proportions between them (Fig. 5). These studies, in addition, show a higher African ancestry with mtDNA than the Y chromosome, indicating that, historically, admixture with Africans has also mostly involved African women.Open in a separate windowFigure 4.The Native American woman known as “Malinche” or Malintzin (her Nahuatl name) was the interpreter and mistress of the Spanish Conquistador, Hernán Cortés. In 1523, she gave him a son, Martín, who is one of the first recorded individuals of mixed Native–European ancestry born in the Americas. Such offspring between immigrant men and Native women were a common occurrence in early colonial Latin America. The drawing shown is from the late 16th century “Codex Tlaxcala” and represents a meeting between the Mexican ruler, Moctezuma, and Hernán Cortés, with Malintzin (on the right) translating.Open in a separate windowFigure 5.Proportion of Native American, European, and African ancestry in 13 Latin American populations estimated using mtDNA and Y-chromosome markers. Samples from urban centers in five countries were examined (Mexico—Mexico City; Guatemala—Oriente; Costa Rica—Central Valley of Costa Rica [CVCR]; Colombia—Peque, Medellín, and Cundinamarca; Chile—Paposo and Quetalmahue; Argentina—Salta, Tucuman, and Tacamarca; and Brazil—Rio Grande do Sul [RGS]). Ancestry proportion (fraction of the pie chart) is color-coded: African (green), European (blue), and Native American (red). (Data for 20 individuals per population are from Wang et al. 2007, Yang et al. 2010, and NN Yang et al. unpubl.)The large variation in ancestry seen across Latin America relates to differences in pre-Columbian Native population density and the pattern of recent immigration into specific regions of the continent. For instance, most studies performed so far have mainly focused on areas with little documented African immigration and consistently show a relatively low African genetic ancestry. In these population samples, the variation in individual European and Native American ancestry is very large, to the extent that it overlaps with that seen in Native population samples (Fig. 6). The variation in individual ancestry seen in these samples thus effaces their designation as “Native” or “non-Native.” This observation punctuates the interest of incorporating admixed Latin American populations, traditionally considered non-Native, into studies on the initial settlement of the continent. Similar to what has been performed in the recent survey by Reich et al. (2012), the inference of ancestry of each genome segment in Latin Americans could be used to focus solely on Native American segments of the genome. This is an avenue of research that is just beginning to be explored and shows great potential for the future. It promises to be of particular importance for the analysis of regions where anthropologically recognizable Native populations and individuals are virtually nonexistent, as they have been absorbed into the current mixed population. This is the case for the many areas that were relatively sparsely populated in pre-Columbian times and, subsequently, received a large flow of immigrants, such as from the Caribbean and many parts of North and South America. Consequently, estimation of individual ancestry along the genome will facilitate denser demographic history analyses across the Americas, as well as a reexamination of the original settlement of the continent based on a more comprehensive population sampling.Open in a separate windowFigure 6.Distribution of individual Native ancestry estimated in samples from Native Americans (shown in blue) and two Latin American urban centers (850 residents of Medellín, Colombia shown in red, and 220 residents of Mexico City, Mexico shown in green). For each of the three population samples, the x-axis indicates the proportion of Native ancestry (in 0.1 unit intervals) and the y-axis indicates the proportion of individuals with that ancestry estimate. The Native American group includes 225 individuals from North, Central, and South America. Ancestry proportions were estimated using autosomal genetic markers. (Data from Florez et al. 2009, Campbell et al. 2011, and Reich et al. 2012.)Other than being informative for addressing questions of population history, the study of Latin American populations promises to facilitate the genetic characterization of biological attributes differentiated among the populations that participated in admixture on the continent. For instance, a range of facial features differ between Native Americans and Europeans, and the genetic study of admixed Latin Americans promises to help in the identification of genes explaining variation in facial appearance. Such research is of interest for understanding disorders of craniofacial development and could also have forensic applications. Another example is type 2 diabetes (T2D), a disease that has a very high frequency in Native Americans and for which a higher risk is associated with increased Native American ancestry. This observation led to the proposal of the “thrifty genotype” hypothesis, which posits that the increased risk of T2D in Native Americans results from genetic adaption to a low-calorie/high-exercise way of life that became detrimental with the recent change to a high-calorie/low-exercise lifestyle (Pollard 2008). The study of large, carefully characterized samples from Latin American populations offers a unique opportunity for conducting a detailed assessment of this hypothesis. The identification of genes explaining the variable frequency of diseases between populations (such as T2D) will be an important step forward in the development of novel, more effective (even individualized) disease-management strategies that account for human population diversity.The overlap of individual genetic ancestry estimates, seen in Latin and Native American populations (Fig. 5), raises the question of the relationship of these estimates to the perception that individuals have of their own ancestry. A recent analysis of a large sample of individuals from five Latin American countries found a highly significant correlation between self-perception and genetically estimated ancestry (Fig. 7). However, this study also found evidence that self-perception is biased. A particularly clear bias involves pigmentation: individuals with greater pigmentation tend to overestimate their Native and African ancestry, whereas individuals with lighter pigmentation tend to overestimate their European ancestry (AR Ruiz-Linares, in press). Statistically significant differences were also observed between countries, pointing to the influence of social factors in self-perception. Consistent with this observation, social scientists have argued that, in Latin America, self-identification as Native or non-Native is often strongly influenced by social cues (Wade 2010).Open in a separate windowFigure 7.Box plots displaying the relationship of individual genetic ancestry estimates to self-perceived ancestry in 7342 Latin Americans (from Mexico, Colombia, Peru, Chile, and Brazil). Self-perception was categorized into 20% bands for African, European, and Native American ancestry. There is a highly significant correlation between the genetic estimate and self-perception for each continental ancestry component. However, there is a trend at higher Native American and African ancestry for self-perception to exceed the genetic estimates. Correspondingly, at lower European ancestry, there is a trend for the genetic estimates to exceed self-perception. Further analyses show that pigmentation impacts on these differences. Individuals with lower skin pigmentation tend to overestimate their European ancestry, whereas individuals with higher pigmentation overestimate their Native American and African ancestries. Orange lines indicate the median and the blue boxes are delimited by the 25th and 75th percentiles. (From AR Ruiz-Linares et al., in press; with permission from the author.)The insights into the initial settlement of the continent provided by the genetic study of Native Americans illustrate the fact that a population sampling that maximizes diversity based on anthropological grounds (such as language) can facilitate investigations concerned with the first settlement of the continent. However, the analysis of intercontinental admixture both in Native and non-Native Latin American populations show some of the complexities of defining human groups, with population labels suggesting a potentially misleading genetic singularity. The biological reality is that of a gradient in the genetic makeup of these populations (and individuals) involving various degrees of mixture between the initial settlers of the continent and more recent immigrants. The genetic diversity of Latin Americans is, thus, a prominent example of the fuzzy meaning of the labels used to refer to human populations. Although these labels can assist in study design and facilitate certain historical inferences, ethnicity, race, and other such terms are social constructs devoid of a clear-cut biological meaning.     

Polarity in Stem Cell Division: Asymmetric Stem Cell Division in Tissue Homeostasis

Many adult stem cells divide asymmetrically to balance self-renewal and differentiation, thereby maintaining tissue homeostasis. Asymmetric stem cell divisions depend on asymmetric cell architecture (i.e., cell polarity) within the cell and/or the cellular environment. In particular, as residents of the tissues they sustain, stem cells are inevitably placed in the context of the tissue architecture. Indeed, many stem cells are polarized within their microenvironment, or the stem cell niche, and their asymmetric division relies on their relationship with the microenvironment. Here, we review asymmetric stem cell divisions in the context of the stem cell niche with a focus on Drosophila germ line stem cells, where the nature of niche-dependent asymmetric stem cell division is well characterized.Asymmetric cell division allows stem cells to self-renew and produce another cell that undergoes differentiation, thus providing a simple method for tissue homeostasis. Stem cell self-renewal refers to the daughter(s) of stem cell division maintaining all stem cell characteristics, including proliferation capacity, maintenance of the undifferentiated state, and the capability to produce daughter cells that undergo differentiation. A failure to maintain the correct stem cell number has been speculated to lead to tumorigenesis/tissue hyperplasia via stem cell hyperproliferation or tissue degeneration/aging via a reduction in stem cell number or activity (Morrison and Kimble 2006; Rando 2006). This necessity changes during development. The stem cell pool requires expansion earlier in development, whereas maintenance is needed later to sustain tissue homeostasis.There are two major mechanisms to sustain a fixed number of adult stem cells: stem cell niche and asymmetric stem cell division, which are not mutually exclusive. Stem cell niche is a microenvironment in which stem cells reside, and provides essential signals required for stem cell identity (Fig. 1A). Physical limitation of niche “space” can therefore define stem cell number within a tissue. Within such a niche, many stem cells divide asymmetrically, giving rise to one stem cell and one differentiating cell, by placing one daughter inside and another outside of the niche, respectively (Fig. 1A). Nevertheless, some stem cells divide asymmetrically, apparently without the niche. For example, in Drosophila neuroblasts, cell-intrinsic fate determinants are polarized within a dividing cell, and subsequent partitioning of such fate determinants into daughter cells in an asymmetric manner results in asymmetric stem cell division (Fig. 1B) (see Fig. 3A and Prehoda 2009).Open in a separate windowFigure 1.Mechanisms of asymmetric stem cell division. (A) Asymmetric stem cell division by extrinsic fate determinants (i.e., the stem cell niche). The two daughters of stem cell division will be placed in distinct cellular environments either inside or outside the stem cell niche, leading to asymmetric fate choice. (B) Asymmetric stem cell division by intrinsic fate determinants. Fate determinants are polarized in the dividing stem cells, which are subsequently partitioned into two daughter cells unequally, thus making the division asymmetrical. Self-renewing (red line) and/or differentiation promoting (green line) factors may be involved.In this review, we focus primarily on asymmetric stem cell divisions in the Drosophila germ line as the most intensively studied examples of niche-dependent asymmetric stem cell division. We also discuss some examples of stem cell division outside Drosophila, where stem cells are known to divide asymmetrically or in a niche-dependent manner.     

Gradients in Planarian Regeneration and Homeostasis

Planarian regeneration was one of the first models in which the gradient concept was developed. Morphological studies based on the analysis of the regeneration rates of planarian fragments from different body regions, the generation of heteromorphoses, and experiments of tissue transplantation led T.H. Morgan (1901) and C.M Child (1911) to postulate different kinds of gradients responsible for the regenerative process in these highly plastic animals. However, after a century of research, the role of morphogens in planarian regeneration has yet to be demonstrated. This may change soon, as the sequencing of the planarian genome and the possibility of performing gene functional analysis by RNA interference (RNAi) have led to the isolation of elements of the bone morphogenetic protein (BMP), Wnt, and fibroblast growth factor (FGF) pathways that control patterning and axial polarity during planarian regeneration and homeostasis. Here, we discuss whether the actions of these molecules could be based on morphogenetic gradients.Freshwater planarians are bilaterally symmetrical metazoans of the phylum Platyhelminthes. These animals are unsegmented, acoelomate, and possess well-defined anteroposterior (AP) and dorsoventral (DV) axes. Along the AP axis, we can distinguish an anterior cephalic region containing the brain and, usually, a pair of eyespots, a central region with a pharynx and a ventral mouth opening, and a posterior tail region (Fig. 1A). Planarians are best known for their ability to regenerate complete animals from tiny fragments of their own bodies in 1 wk (for review, see Saló and Baguñá 2002; Reddien and Sánchez-Alvarado 2004; Saló 2006; Sánchez-Alvarado 2006). This ability has attracted the interest of many scientists since long ago (Pallas 1774; Johnson 1822; Morgan 1901). Planarian regeneration requires the production of new tissue from the unique proliferative and pluripotent stem cells known as neoblasts (Handberg-Thorsager et al. 2008). After amputation, neoblasts close to the wound proliferate, giving rise to the regenerative blastema, defined as the unpigmented tissues where the missing tissues will differentiate (Fig. 1B–E). Remarkably, planarian pieces cut at any level along any of its axes can regenerate a whole worm, perfectly proportionate in only a few days (Fig. 1F). The process of tissue regeneration in the wound region from proliferating neoblasts was termed epimorphosis. In addition, a repatterning of the whole organism is required to recover a complete and proportionate regenerated planarian. This process of remodeling old tissues was termed morphallaxis (Morgan 1901). Together, with the initial studies on planarian regeneration, the first hypotheses suggesting a role of morphogenetic gradients in this process were proposed based on the observation of a differential regenerative capacity along the AP axis (Morgan 1901; Child 1911; Huxley and de Beer 1934).Open in a separate windowFigure 1.Regenerative capacity of freshwater planarians. (A) Schmidtea mediterranea planarian (top left). (e) Eyespots, (ph) pharynx. Bar, 1 mm. (B–E) Tail pieces at various stages of regeneration (top right). The white tissue in the most anterior tip is the regenerative blastema. Two small eyespots are evident within it after 5 d of regeneration. (F) Planarians display unique regenerative capacities, as any small fragments from almost anywhere can regenerate a new organism in 2 wk. In this diagram, we summarize the main types of planarian regeneration: (1) Terminal regeneration: After transverse sectioning, the anterior end (red line) will regenerate the missing head, whereas the posterior end (green line) will regenerate the missing tail. This indicates that the remaining tissue is polarized and knows what is missing. (2) Lateral regeneration: After longitudinal sectioning (blue line), the old tissue regenerates the missing lateral half. (3) Intercalary regeneration: After joining two distal pieces produced by transverse sections, planarians intercalate the missing region. In that case, cells from each piece participate equally in the production of an intercalary blastema (Saló and Baguñà 1985).     

Apoptotic and Nonapoptotic Caspase Functions in Animal Development

A developing animal is exposed to both intrinsic and extrinsic stresses. One stress response is caspase activation. Caspase activation not only controls apoptosis but also proliferation, differentiation, cell shape, and cell migration. Caspase activation drives development by executing cell death or nonapoptotic functions in a cell-autonomous manner, and by secreting signaling molecules or generating mechanical forces, in a noncell autonomous manner.Programmed cell death or apoptosis occurs widely during development. During C. elegans development, 131 cells die by caspase CED-3-dependent apoptosis; however, ced-3 mutants do not show significant developmental defects (Ellis and Horvitz 1986). In contrast, studies on caspase mutants in mouse and Drosophila have revealed caspases’ roles in development. During development, cells are exposed to extrinsic and intrinsic stresses, and caspases are activated as one of multiple stress responses that ensure developmental robustness (Fig. 1). Caspases actively regulate animal development through both apoptosis and nonapoptotic functions that involve cell–cell communication in developing cell communities (Miura 2011). This chapter focuses on the in vivo roles of caspases in development and regeneration.Open in a separate windowFigure 1.Caspase activation during development. An embryo undergoes intrinsic and extrinsic stress, which activates caspases to execute both apoptotic and nonapoptotic functions, including cell differentiation and dendrite pruning. Apoptotic cells affect the shape and behavior of their neighboring cells. Caspase-activated cells are shown in dark gray.     

DNA-Pairing and Annealing Processes in Homologous Recombination and Homology-Directed Repair

The formation of heteroduplex DNA is a central step in the exchange of DNA sequences via homologous recombination, and in the accurate repair of broken chromosomes via homology-directed repair pathways. In cells, heteroduplex DNA largely arises through the activities of recombination proteins that promote DNA-pairing and annealing reactions. Classes of proteins involved in pairing and annealing include RecA-family DNA-pairing proteins, single-stranded DNA (ssDNA)-binding proteins, recombination mediator proteins, annealing proteins, and nucleases. This review explores the properties of these pairing and annealing proteins, and highlights their roles in complex recombination processes including the double Holliday junction (DhJ) formation, synthesis-dependent strand annealing, and single-strand annealing pathways—DNA transactions that are critical both for genome stability in individual organisms and for the evolution of species.A central step in the process of homologous recombination is the formation of heteroduplex DNA. In this article, heteroduplex DNA is defined as double-stranded DNA that arose from recombination, in which the two strands are derived from different parental DNA molecules or regions. The two strands of the heteroduplex may be fully complementary in sequence, or may contain small regions of noncomplementarity embedded within their otherwise complementary sequences. In either case, Watson-Crick base pairs must stabilize the heteroduplex to the extent that it can exist as free DNA following the dissociation of the recombination proteins that promoted its formation.The ability to form heteroduplex DNA using strands from two different parental DNA molecules lies at the heart of fundamental biological processes that control genome stability in individual organisms, inheritance of genetic information by their progeny, and genetic diversity within the resulting populations (Amunugama and Fishel 2012). During meiosis, the formation of heteroduplex DNA facilitates crossing-over and allelic exchange between homologous chromosomes; this process ensures that progeny are not identical clones of their parents and that sexual reproduction between individuals will result in a genetically diverse population (see Lam and Keeney 2015; Zickler and Kleckner 2015). Heteroduplex DNA generated by meiotic COs also ensures proper segregation of homologous chromosomes, so that each gamete receives a complete but genetically distinct set of chromosomes (Bascom-Slack et al. 1997; Gerton and Hawley 2005). In mitotic cells, heteroduplex DNA formation between sister chromatids is essential for homology-directed repair (HR) of DNA double-strand breaks (DSBs), stalled replication forks, and other lesions (Maher et al. 2011; Amunugama and Fishel 2012; Mehta and Haber 2014). Prokaryotic organisms also generate heteroduplex DNA to perform HR transactions, and to promote genetic exchanges, such as occur during bacterial conjugation (Cox 1999; Thomas and Nielsen 2005).Fundamentally, heteroduplex DNA generation involves the formation of tracts of Watson-Crick base pairs between strands of DNA derived from two different progenitor (parental) DNA molecules. Mechanistically, the DNA transactions giving rise to heteroduplex may involve two, three, or four strands of DNA (Fig. 1). DNA annealing refers to heteroduplex formation from two complementary (or nearly complementary) molecules or regions of single-stranded DNA (ssDNA) (Fig. 1A). DNA annealing may occur spontaneously, but it is promoted in vivo by certain classes of annealing proteins. Three-stranded reactions yielding heteroduplex DNA proceed by a different mechanism referred to as DNA pairing, strand invasion, or strand exchange. These reactions involve the invasion of a duplex DNA molecule by homologous (or nearly homologous) ssDNA. The invading DNA may be completely single stranded, as is often the case in in vitro assays for DNA-pairing activity (Fig. 1B) (Cox and Lehman 1981). Under physiological conditions, however, the invading ssDNA is contained as a single-stranded tail or gap within a duplex (Fig. 1C,D). DNA-pairing reactions are promoted by DNA-pairing proteins of the RecA family (Bianco et al. 1998), and proceed via the formation of D-loop or joint molecule intermediates that contain the heteroduplex DNA (Fig. 1B–D). Three-stranded reactions may also be promoted by exonuclease/annealing protein complexes found in certain viruses. Four-stranded reactions generating heteroduplex DNA involve branch migration of a Holliday junction (Fig. 1D). In practice, a four-stranded reaction must be initiated by a three-stranded pairing reaction catalyzed by a DNA-pairing protein, after which the heteroduplex is extended into duplex regions through the action of the DNA-pairing protein or of an associated DNA helicase/translocase (Das Gupta et al. 1981; Kim et al. 1992; Tsaneva et al. 1992).Open in a separate windowFigure 1.Common DNA annealing and pairing reactions. (A) Simple annealing between two complementary molecules of single-stranded DNA to form a heteroduplex. (B) Three-stranded DNA-pairing reaction of the type used for in vitro assays of RecA-family DNA-pairing proteins. The single-stranded circle is homologous to the linear duplex. Formation of heteroduplex (red strand base-paired to black) requires protein-promoted invasion of the duplex by the ssDNA to form a joint molecule or D-loop (i). The length of the heteroduplex may be extended by branch migration (ii). (C) Three-stranded DNA-pairing reaction of the type used for high-fidelity repair of DNA DSBs in vivo. The invading strand is the ssDNA tail of a resected DSB. The 3′ end of the invading strand is incorporated into the heteroduplex within the D-loop intermediate. (D) Example of a four-stranded DNA-pairing transaction that is initiated by a three-stranded pairing event and extended by branch migration. The ssDNA in a gapped duplex serves as the invading strand to generate a joint molecule (i), reminiscent of the reaction shown in panel B. Protein-directed branch migration may proceed into the duplex region adjacent to the original gap, generating α-structure intermediates (ii), or eventually a complete exchange of strands (iii).     

Cyanobacterial Heterocysts

Many multicellular cyanobacteria produce specialized nitrogen-fixing heterocysts. During diazotrophic growth of the model organism Anabaena (Nostoc) sp. strain PCC 7120, a regulated developmental pattern of single heterocysts separated by about 10 to 20 photosynthetic vegetative cells is maintained along filaments. Heterocyst structure and metabolic activity function together to accommodate the oxygen-sensitive process of nitrogen fixation. This article focuses on recent research on heterocyst development, including morphogenesis, transport of molecules between cells in a filament, differential gene expression, and pattern formation.Organisms composed of multiple differentiated cell types can possess structures, functions, and behaviors that are more diverse and efficient than those of unicellular organisms. Among multicellular prokaryotes, heterocyst-forming cyanobacteria offer an excellent model for the study of cellular differentiation and multicellular pattern formation. Cyanobacteria are a large group of Gram-negative prokaryotes that perform oxygenic photosynthesis. They have evolved multiple specialized cell types, including nitrogen-fixing heterocysts, spore-like akinetes, and the cells of motile hormogonia filaments. Of these, the development of heterocysts in the filamentous cyanobacterium Anabaena (also Nostoc) sp. strain PCC 7120 (hereafter Anabaena PCC 7120) has been the best studied. Heterocyst development offers a striking example of cellular differentiation and developmental biology in a very simple form: Filaments are composed of only two cell types and these are arrayed in a one-dimensional pattern similar to beads on a string (Figs. 1 and ​and22).Open in a separate windowFigure 1.Heterocyst development in Anabaena PCC 7120. (A) Anabaena PCC 7120 grown in medium containing a source of combined nitrogen grows as filaments of photosynthetic vegetative cells. (B) In the absence of combined nitrogen, heterocysts differentiate at semiregular intervals, forming a developmental pattern of single heterocysts every 10 to 20 vegetative cells along filaments. Heterocysts are often larger than vegetative cells, have a thicker multilayered envelope, and usually contain cyanophycin granules at their poles adjacent to a vegetative cell.Open in a separate windowFigure 2.Heterocyst development in Anabaena PCC 7120. Filaments of the wild type carrying a patS-gfp reporter grown in medium containing nitrate are composed of vegetative cells (A), and have undergone heterocyst development 1 d after transfer to medium without combined nitrogen (B). A patS mutant strain carrying the same patS-gfp reporter grown in media containing nitrate contains a small number of heterocysts (C), and 1 d after transfer to medium without combined nitrogen shows a higher than normal frequency of heterocysts and an abnormal developmental pattern (D). (A, B, C, D) Merged DIC (grayscale), autofluorescence of photosynthetic pigments (red), and patS-gfp reporter fluorescence (green) microscopic images; arrowheads indicate heterocysts; asterisks indicate proheterocysts; size bar, 5 µm. (E, F) Transmission electron micrographs of wild-type vegetative cells (V) and a heterocyst (H) at the end of a filament; T, thylakoid membranes; PS, polysaccharide layer; GL, glycolipid layer; C, polar cyanophycin granule; size bar, 0.2 µm.Many cyanobacterial species are capable of nitrogen fixation. However, oxygenic photosynthesis and nitrogen fixation are incompatible processes because nitrogenase is inactivated by oxygen. Cyanobacteria mainly use two mechanisms to separate these activities: a biological circadian clock to separate them temporally, and multicellularity and cellular differentiation to separate them spatially. For example, the unicellular Cyanothece sp. strain ATCC 51142 stores glycogen during the day and fixes nitrogen at night (Toepel et al. 2008), whereas the filamentous Trichodesmium erythraeum IMS101 fixes nitrogen during the day in groups of specialized cells (Sandh et al. 2009). Heterocyst-forming cyanobacteria differentiate highly specialized cells to provide fixed nitrogen to the vegetative cells in a filament.In the presence of a source of combined nitrogen such as nitrate or ammonium, Anabaena PCC 7120 grows as long filaments containing hundreds of photosynthetic vegetative cells. In the absence of combined nitrogen, it produces heterocysts, which are terminally differentiated nitrogen-fixing cells that form at semiregular intervals between stretches of vegetative cells to produce a multicellular pattern of single heterocysts every ten to twenty vegetative cells along filaments (Figs. 1 and ​and2).2). Some heterocyst-forming cyanobacteria show different regulation or display different developmental patterns but these topics are beyond the scope of this article. Heterocyst development involves integration of multiple external and internal signals, communication between the cells in a filament, and temporal and spatial regulation of genes and cellular processes. The study of heterocyst development in Anabaena PCC 7120 has proven to be an excellent model for the study of cell fate determination, pattern formation, and differential gene expression during prokaryotic multicellular evelopment. Various aspects of heterocyst development, signaling, and regulation have been the subject of several recent reviews (Meeks and Elhai 2002; Forchhammer 2004; Herrero et al. 2004; Zhang et al. 2006; Aldea et al. 2008; Zhao and Wolk 2008).Although beyond the scope of this article, it should be noted that cyanobacteria have recently attracted increased attention because of their important roles in environmental carbon and nitrogen fixation (Montoya et al. 2004), and their potential for providing renewable chemicals and biofuels (Dismukes et al. 2008).