The power of Drosophila in modeling human disease mechanisms

Six years ago, DMM launched a subject collection called ‘Drosophila as a Disease Model’. This collection features Review-type articles and original research that highlight the power of Drosophila research in many aspects of human disease modeling. In the ensuing years, Drosophila research has further expanded to capitalize on genome editing, development of resources, and further interest in studying rare disease mechanisms. In the current issue of DMM, we again highlight the versatility, breadth, and scope of Drosophila research in human disease modeling and translational medicine. While many researchers have embraced the power of the fly, many more could still be encouraged to appreciate the strengths of Drosophila and how such research can integrate across species in a multi-pronged approach. Only when we truly acknowledge that all models contribute to our understanding of human biology, can we take advantage of the scope of current research endeavors.

Summary: This Editorial encourages us to embrace the power of the fly in studying human disease and highlights how Drosophila studies can be integrated with research in other species to further our understanding of human biology.

For over a century, scientists have used the fruit fly to learn about fundamental and evolutionarily conserved genetic and cellular processes. The pioneering work of Thomas Hunt Morgan and his students, in the early 20th century, proved that genes are located on chromosomes and led to the first chromosome linkage maps (Morgan, 1910). In the 1980s, Ed Lewis, Christiane Nüsslein-Volhard and Eric Wieschaus showed that individual genes could be mutated to cause characteristic embryonic patterning defects (Lewis, 1978; Nüsslein-Vollhard and Wieschaus, 1980). Their genetic studies allowed them to order genes within functional pathways through epistasis analyses. The genes they identified have counterparts across species and play key roles in development and disease from flies to humans. Indeed, much of the molecular circuitry for key signaling pathways, such as RAS, Notch, Hedgehog and Wnt, was elucidated in Drosophila (Ashton-Beaucage and Therrien, 2017; Bejsovec, 2018; Ingham, 2018; Salazar and Yamamoto, 2018). This rich history has established Drosophila as a powerful tool in biology, paving the way for further advances in basic and translational research.     

Modelling infectious disease to support human health

During the current COVID-19 pandemic, there has been renewed scientific and public focus on understanding the pathogenesis of infectious diseases and investigating vaccines and therapies to combat them. In addition to the tragic toll of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we also recognize increased threats from antibiotic-resistant bacterial strains, the effects of climate change on the prevalence and spread of human pathogens, and the recalcitrance of other infectious diseases – including tuberculosis, malaria, human immunodeficiency virus (HIV) and fungal infections – that continue to cause millions of deaths annually. Large amounts of funding have rightly been redirected toward vaccine development and clinical trials for COVID-19, but we must continue to pursue fundamental and translational research on other pathogens and host immunity. Now more than ever, we need to support the next generation of researchers to develop and utilize models of infectious disease that serve as engines of discovery, innovation and therapy.

Summary: This Editorial considers how knowledge from animal and other models of infectious disease can impact our understanding of human biology and potential therapies, focusing largely on zebrafish. It also highlights ways in which DMM is supporting these areas.

As an Editor at Disease Models & Mechanisms (DMM) and an academic researcher using zebrafish as a model to study tuberculosis, it is especially exciting to read and publish research in zebrafish to obtain, in a whole, live vertebrate, insights into infectious diseases and therapies (Box 1). Indeed, zebrafish provide a remarkable vertebrate model for many questions related to infectious disease. Embryos and larvae are optically transparent, enabling microscopy of both pathogen and host that would be more challenging or cumbersome in other systems (Fig. 1). Knock-in of fluorescent tags at endogenous loci allows direct and detailed in vivo visualization of the host immune response (Cronan et al., 2018). Both forward and reverse genetic approaches for understanding infection are straightforward and are buttressed by the high-throughput capabilities of this model, in which a single tank of adult zebrafish can produce hundreds of embryos per week. Furthermore, chemical biology screens and interventions using intact, living animals are uniquely accessible to researchers, as zebrafish larvae and embryos are permeable to diverse small molecules and fit within a single well of 96-well and 384-well plates (Patton et al., 2021). Open in a separate windowFig. 1.Zebrafish larva infected with fluorescent Mycobacterium abscessus expressing TdTomato, shown in red. Image courtesy of Matt Johansen (Johansen et al., 2021).Box 1. DMM highlights zebrafish advancing knowledge in infectious diseaseRecent publications in DMM show the potential of the zebrafish model system to provide new or fuller insights into infectious diseases and therapies. One question being addressed is how basic cell-autonomous immune processes function in the context of a full organism. Various Reviews have highlighted what we have learned about the role of pyroptosis in host defence against bacterial infections (Brokatzky and Mostowy, 2022), as well as advances in understanding the diverse roles that macrophages and neutrophils play during the initial response to a variety of infectious and inflammatory stimuli (Rosowski, 2020). Zebrafish can also provide models for parasitic diseases that are relatively neglected, and we were pleased to publish a zebrafish model that provides insight into Toxoplasma pathogenesis, particularly the in vivo interactions of Toxoplasma with macrophages (Yoshida et al., 2020). Research dissecting the role of host immune cells in pathogen responses can be further potentiated by new tools, such as those developed by the Lieschke laboratory using macrophage and neutrophil-specific Cas9 driver lines to allow cell-specific genetic perturbation (Isiaku et al., 2021).Non-tuberculous mycobacteria causing pulmonary disease are a growing threat worldwide, with an antibiotic resistance profile that makes them very difficult to treat (Stout et al., 2016; Vinnard et al., 2016). An exploration of phage therapy for non-tuberculous mycobacteria in the zebrafish provides new insights into exciting clinical work that bookends this publication (Johansen et al., 2021). Engineered bacteriophages targeting specific strains of Mycobacterium abscessus have now been used clinically in cases of advanced lung disease (Dedrick et al., 2019; Nick et al., 2022). In other work, Habjan et al. employed the zebrafish mycobacterial infection model as an early screening step for anti-tuberculosis hits from in vitro screens that might have the best chance for in vivo translation. Following up on a screen for novel in vitro activity against Mycobacterium tuberculosis that identified ∼240 compounds, they identified 14 compounds with good in vivo activity. Impressively, they went on to identify the target of the strongest in vivo hit as being a mycobacterial aspartyl-tRNA synthase through screening for resistant mutants in both Mycobacterium marinum and Mycobacterium tuberculosis (Habjan et al., 2021).Drug screens, like those discussed above, are possible due to the permeability of the zebrafish to small molecules, which also allows creative ways to control the induction of host cytokines. DMM published an approach that enables drug-inducible, tissue-specific, titratable expression of different cytokines (Ibrahim et al., 2020). Harnessing this permeability in zebrafish can also enable detailed exploration of the effects of drugs, such as broadly used glucocorticoids, on specific innate immune cell types (Xie et al., 2019).The zebrafish has also been used as a model to understand infectious disease therapies targeting the pathogen directly. A recent paper describes the in vivo efficacy of nanoparticle-based delivery of lipophilic antibiotics, as well as use of the zebrafish to screen different formulations (Knudsen Dal et al., 2022). Finally, in the adult zebrafish sphere, a recent Review focused on how zebrafish can inform vaccine development strategies (Saralahti et al., 2020).These recent publications highlight some of the strengths of the zebrafish model for infectious disease research. DMM aims to be at the forefront in encouraging scientists and clinicians to leverage these insights for future therapies.Although efforts in zebrafish are often recognized and valued within the model organism community and beyond, it can sometimes be hard to break through to the world of clinical research. I vividly remember the excitement of being invited to present my work as a starting assistant professor at an early-career researcher lunch with a prominent visiting scientist, only to have my research and plans dismissed with some variation of “Well, why don''t you try to figure out what''s actually going on in people?”.Indeed, this is what many zebrafish researchers are ultimately trying to do by a different route. The goal of harnessing the knowledge we generate in models to impact human biology and therapies is an important part of the scientific enterprise. Many of us want and expect our findings to be relevant beyond the context of a model system. In my field, it has been exciting to see work in the zebrafish emerge that has led to the discovery of fundamentally conserved features of tuberculosis and host immunity – from zebrafish to humans – and has since translated to ongoing clinical trials.However, although we might hope that our work will be inherently understood and utilized in the clinical context, maximizing the potential of this research requires community advocates and communicators to help place the work in context. This can be achieved through ongoing dialogue among researchers, clinicians and patients to understand medical needs and perspectives. For example, DMM and The Company of Biologists have been long-time supporters of societies, such as the Zebrafish Disease Models Society, which focuses on the translational potential of zebrafish for understanding human disease and for developing new therapies, including some being investigated in clinical trials.Thus, it is useful to consider the following three broad themes when using model organisms in infectious disease research:

1. Conserved host–pathogen interactions in model systems. Although we all recognize, even at a strictly visual level, the many differences between the biology of a model organism and human biology, there is fundamentally conserved biology to be explored. Immune signalling pathways and underlying principles, as well as molecular and cellular details, first discovered and dissected in worms, flies, fish, mice and other model organisms, have translated remarkably well to human biology in many cases.
2. Model diversity. Divergent biology – in addition to being fascinating and important for the sake of knowledge itself – also leads to vital new insights and therapeutic approaches. As just one example, bacteriophages were instrumental in the discovery of fundamental aspects of gene regulation, have been used to facilitate genetic manipulation of seemingly genetically intractable pathogens, and are now being engineered and deployed therapeutically. And the study of bacterial–bacteriophage interactions of course led to all the advances made possible by CRISPR. These and many other examples from models that diverge from humans all support open-mindedness in science and emphasize the strength of laboratories taking diverse approaches and using diverse models. Pressing questions and opportunities in this realm are many, including investigation of how some non-human immune systems – those of bats, as just one example – permit asymptomatic tolerance of viruses that may be pathogenic in humans (Hayman, 2019). Which animal species restrict human pathogens via immune mechanisms that might eventually be harnessed therapeutically? Some of these topics will be prominent in a 2023 meeting organized by DMM entitled ‘Infectious Diseases Through an Evolutionary Lens’, which will take place in London at the British Medical Association House (Fig. 2).Open in a separate windowFig. 2.DMM''s 2023 meeting is entitled ‘Infectious Diseases Through an Evolutionary Lens’ and will take place in London at the British Medical Association House. Register your interest here: https://www.biologists.com/infectious-diseases-through-an-evolutionary-lens-contact-form/.
3. Engineering preclinical and predictive models of infectious disease. With advances in gene editing and the ability to make specific base edits, it is possible to precisely model human variants in an in vivo context during infection. Organisms like the zebrafish can provide useful models to delve into the specific consequences of these variants. Orthogonal approaches include mammalian animal models and advanced human cell models (Leist et al., 2020; van der Vaart et al., 2021). Discussion between scientists doing this preclinical work and clinical collaborators will be needed to determine to what degree the model recapitulates human disease and how these models can be used to advance new therapies. Recently, we have seen some of the landscape for clinical trials change, and in public health emergencies, collaborations would ideally accelerate the time from discovery to clinic. Again, this will require dialogue with and buy-in from clinical researchers to put together rigorous clinical trials.

DMM seeks to create and contribute to the ongoing conversations among and between basic scientists, clinical researchers and clinicians, with insights and criticisms from each of these domains. By highlighting rigorous, high-quality science in these areas, we hope to contribute to improved understanding of infectious diseases and new approaches to treatment.     

Envisioning the next human genome reference

Summary: We provide an Editorial perspective on approaches to improve ethnic representation in the human genome reference sequence, enabling its widespread use in genomic studies and precision medicine to benefit all peoples.

This year marks the 20th anniversary of the announced completion of the draft human genome sequence. The reference genome was a transformative accomplishment for human biological and medical research and is often referred to as biology''s moonshot. Over the past 20 years, the availability of this reference, and its refinement, has had the predicted transformative impact on our understanding of human genetic diseases, and, in many ways, has revolutionized the practice of medicine and medical diagnosis. These advances are mainly due to the emergence and refinement of rapid sequencing technology, which has facilitated our ability to generate genomic data, and to corresponding advances in computational analysis of these data, which have solidified the significant role of genomic alterations in disease etiology. Along these lines, large international projects have enriched our understanding of human genomic diversity in the context of cancer (Campbell et al., 2020), psychiatric genetics (Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018; Cleynen et al., 2021), autism (Satterstrom et al., 2020; Trost et al., 2020) and many other diseases. Such studies have mainly catalogued individual and ancestry-based variation in human genomes, albeit to a limited extent. The inherent limitation in scope has been reflective of a predominant focus on populations of European ancestry in the earliest studies, such as the 1000 Genomes Project. More recent attempts to address these disparities have illuminated the challenges in recruiting diverse populations that either have a justifiable lack of trust in medical research or have cultural complexities regarding consent to participate. By improving diversity and inclusion in these studies, there would be increased hope that genomic studies will more broadly benefit populations. In order for the human genome and genomics to have a more significant and equitable impact in the future, accordingly, there is much more to be done. Medical and scientific communities need to consult with and listen to diverse populations and cultures to understand their concerns and needs, and, importantly, to make corresponding changes in our research practices that ensures accountability to these groups. Open in a separate windowImage reproduced under the terms of the Pixabay License.Ongoing large-scale population studies that link with individual clinical information are beginning to shape newer capabilities in predicting complex genetic disease susceptibility, primarily focused on developing and testing polygenic risk scores (Shen et al., 2020; Vujkovic et al., 2020; Riveros-Mckay et al., 2021; Weale et al., 2021). These efforts have the potential to radically change the practice of medicine, from a reactive to a proactive model of care delivery, based on an individual''s likelihood to experience predicted health challenges during their life course. As such, not only is current genomics-based diagnosis being imperiled by a lack of understanding of genomic variation based on ancestry (Sirugo et al., 2019), but future health care aspects also will be compromised in an ancestry-specific way, further compounding the impact of systemic racism that continues to make ethnic minorities more vulnerable in this setting (Yudell et al., 2020). In aggregate, this means that health disparities in many underserved populations will continue. In addition to these disparities in genomic representation, we also still lack a fundamental understanding across all ancestries, of what genotypes define as ‘healthy’ relative to our significant and growing understanding of ‘diseased’.There is renewed hope as newer projects strive to improve inclusivity, and here we highlight several examples arising in the United States. The National Institutes of Health (NIH)’s All of Us Research Program has set laudable goals for inclusion of diverse ethnic groups based on recent metrics, wherein over 50% of the currently enrolled 394,000 participants are ethnic minorities. This is a promising beginning, and, with a planned recruitment of 1 million participants, it will be interesting to see the final percentages toward the stated goal. More recently, the NIH posted a request for applications in support of research leading to the creation of best practices for the study of population identifiers. Local projects that focus on specific populations are also emerging, with a variety of funding mechanisms. For example, a study funded by the New York Genome Center plans to enroll minority participants from the broad diversity found throughout the New York City metropolitan area, with an aim to sequence whole genomes and collect health-related information, as discussed by Harold Varmus, one of the study''s leaders (Varmus, 2019). In Columbus, Ohio, the Institute for Genomic Medicine has opened an Institutional Review Board-approved study to consent, produce and database whole-genome sequences from unrelated individuals of Somali descent, to better inform our genomics-based diagnostic efforts for Somali children. Similarly, at Yale University, the Generations Project aims to increase diversity by recruiting in the Connecticut area, which is closely aligned with diversity in US consensus metrics. The exome sequencing and genotyping data from this project will be linked to electronic health records, allowing an opportunity to study and advance genomic health in under-represented minorities. Olufunmilayo Olopade, at the University of Chicago, has also discussed her work investigating genetic risk factors for breast cancer in Black women in studies based in Chicago and West Africa that aim to improve early detection, prevention and treatment in these populations (Olopade, 2021). Similar efforts outside the United States include the Human Heredity and Health in Africa Initiative (H3Africa), GenomeAsia 100K, ChileGenomico and the oriGen Project based in Mexico, among others.Technology continues to impact our human genome reference, predominantly using long-read single-molecule sequencing technologies to generate data, and algorithms capable of assembling these reads into long stretches of human chromosomes, permitting a more complete understanding of structural variation and unique content. Recently, an ‘end-to-end’ assembly of a complete hydatidiform mole cell line was reported, providing contiguity across centromeric and other complex repeats in the human genome, as described in a preprint (Nurk et al., 2021). However, the ancestry of this sample is European. Importantly, the Pangenome Project will aim to produce high-quality long-read sequencing for 300 individuals originally profiled in the 1000 Genomes Project. These comprehensive reference genomes will also include sequences of highly repetitive regions, including centromeres, segmental duplications and ribosomal DNA (rDNA) arrays on telomeres. In addition, the population diversity provided by these genomes will give researchers the option to choose a reference that is more closely related to any given sequenced individual, resulting in improved variant discovery.In addition to the influence of genomic technology, we have branched out from sole focus on DNA sequence to cataloguing RNA expression, isoforms and other types of characterization by applying next-generation and single-molecule sequencing, which, when integrated with DNA information, can provide significant insights into the sequences actively being expressed in tissues, as well as those being silenced by chromatin conformation or methylation. Such studies reveal that there is much more to be learned, and emphasize the importance of cataloguing normal tissue gene expression, which is available at GTEx, the Allen Brain Atlas and other internet resources. Exquisite new knowledge of gene expression profiles at the single-cell level from normal and diseased human tissue is emerging from the Human Cell Atlas projects, revealing the intricacies of human biology at high resolution (Ponting, 2019; Lindeboom et al., 2021).Yet, the concern about inclusion persists, even for these newest technological avenues that may indeed reveal important, ancestry-relevant differences with respect to disease susceptibility, physiologic specificity, pharmacogenomics and other pertinent areas (Okada et al., 2018). Without broadening the scope of diversity, we are concerned that individuals and populations will be left behind in many aspects of genomic medicine, effectively broadening disparities. Considering worldwide disparities that exist, such as poor access to health care, even in countries with high income and/or universal health care, the question remains about how to effectively foster inclusion and ensure that under-represented populations will benefit from expanded genomic research. Several strategies for increasing diversity and inclusion have been published (Cooke Bailey et al., 2020; Essien and Ufomata, 2021; Rotimi and Adeyemo, 2021; Nature Editorial, 2021). Here, we would like to highlight the following approaches. First, diversity in research subjects and samples starts with a diverse workforce at all levels, including leadership of major consortium efforts. To enable the creation of a diverse workforce, researchers need to engage with these communities to encourage and support them in pursuing such career paths and overcoming institutional barriers to achieve these goals. Researchers from under-represented groups that truly understand the communities being studied should have the opportunity to participate at all levels of a project, including leading the project and consenting participants (Bonham and Green, 2021). This facilitates surmounting socio-economic and cultural barriers that make it difficult to recruit under-represented minorities and engages the study team to meet diversity recruitment goals, while ensuring that the interpretation and outcomes of research are broadly beneficial. Second, there needs to be increased funding of institutions with diverse staff and students, such as Historically Black Colleges and Universities or community colleges with 2-year associate programs, as well as internship programs that bring minority students from inner-city high schools into genomics laboratories to learn about genomics research and its applicability to human health. Such programs ensure that leadership opportunities and training in genomics will directly benefit the communities that we intend to recruit. Equally important in this regard is education directed at researchers and medical providers that illuminates ongoing issues concerning racism, diversity and inclusion in science and health care. Third, long-term funding must be dedicated to build infrastructure and collaborative networks to enable the facile recruitment of diverse cohorts. H3Africa is a good model that could be replicated in other under-represented regions across the world, including diverse populations in large inner-city settings, emphasizing needed focus on consultation within these communities to understand their wants, needs and concerns regarding genetics and genomics. Lastly, funding agencies need to switch mindsets from having diversity as an optional goal to being a measurable milestone that must be met. The Human Cell Atlas in their recent funding round for the Pediatric Cell Atlas provides one example of explicit ancestry recruitment goals. Longer term, we must take responsibility to put in place mechanisms that both ensure accessibility to data and quantify the benefit of these studies to all populations.In reflecting on the 20 years since the published draft human genome, it is time to recognize that the combination of technologies, computational algorithms, and the diversity and inclusion of participants gives us the opportunity, this time around, to design cohort studies to benefit ALL of us. Certainly, there is a responsibility for journals, such as DMM, to address the issue of diversity and inclusion, by encouraging the publication of research that advances our understanding of diseases over-represented in individuals of diverse ancestries, and also encouraging reviewers to be conscious that access to technology is not equivalent in all countries, when requesting revisions for publication. DMM''s policies include aims to engage diverse and inclusive groups of authors, reviewers, Editors, Editorial Board members, readers and the communities being studied, and the journal is a signatory of the Royal Society of Chemistry''s initiative ‘Joint commitment for action on inclusion and diversity in publishing’. Journals can also seek out and publish pieces that address these important (and sometimes difficult) conversations, and openly discuss the ongoing challenges as well as approaches employed by others, as we strive to identify solutions that benefit everyone.     

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).     

Molecular Bases of Cell–Cell Junctions Stability and Dynamics

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

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.     

The nuclease activity of DNA2 promotes exonuclease 1–independent mismatch repair

The DNA mismatch repair (MMR) system is a major DNA repair system that corrects DNA replication errors. In eukaryotes, the MMR system functions via mechanisms both dependent on and independent of exonuclease 1 (EXO1), an enzyme that has multiple roles in DNA metabolism. Although the mechanism of EXO1-dependent MMR is well understood, less is known about EXO1-independent MMR. Here, we provide genetic and biochemical evidence that the DNA2 nuclease/helicase has a role in EXO1-independent MMR. Biochemical reactions reconstituted with purified human proteins demonstrated that the nuclease activity of DNA2 promotes an EXO1-independent MMR reaction via a mismatch excision-independent mechanism that involves DNA polymerase δ. We show that DNA polymerase ε is not able to replace DNA polymerase δ in the DNA2-promoted MMR reaction. Unlike its nuclease activity, the helicase activity of DNA2 is dispensable for the ability of the protein to enhance the MMR reaction. Further examination established that DNA2 acts in the EXO1-independent MMR reaction by increasing the strand-displacement activity of DNA polymerase δ. These data reveal a mechanism for EXO1-independent mismatch repair.

The mismatch repair (MMR) system has been conserved from bacteria to humans (1, 2). It promotes genome stability by suppressing spontaneous and DNA damage-induced mutations (1, 3, 4, 5, 6, 7, 8, 9, 10, 11). The key function of the MMR system is the correction of DNA replication errors that escape the proofreading activities of replicative DNA polymerases (1, 4, 5, 6, 7, 8, 9, 10, 12). In addition, the MMR system removes mismatches formed during strand exchange in homologous recombination, suppresses homeologous recombination, initiates apoptosis in response to irreparable DNA damage caused by several anticancer drugs, and contributes to instability of triplet repeats and alternative DNA structures (1, 4, 5, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18). The principal components of the eukaryotic MMR system are MutSα (MSH2-MSH6 heterodimer), MutLα (MLH1-PMS2 heterodimer in humans and Mlh1-Pms1 heterodimer in yeast), MutSβ (MSH2-MSH3 heterodimer), proliferating cell nuclear antigen (PCNA), replication factor C (RFC), exonuclease 1 (EXO1), RPA, and DNA polymerase δ (Pol δ). Loss-of-function mutations in the MSH2, MLH1, MSH6, and PMS2 genes of the human MMR system cause Lynch and Turcot syndromes, and hypermethylation of the MLH1 promoter is responsible for ∼15% of sporadic cancers in several organs (19, 20). MMR deficiency leads to cancer initiation and progression via a multistage process that involves the inactivation of tumor suppressor genes and action of oncogenes (21).MMR occurs behind the replication fork (22, 23) and is a major determinant of the replication fidelity (24). The correction of DNA replication errors by the MMR system increases the replication fidelity by ∼100 fold (25). Strand breaks in leading and lagging strands as well as ribonucleotides in leading strands serve as signals that direct the eukaryotic MMR system to remove DNA replication errors (26, 27, 28, 29, 30). MMR is more efficient on the lagging than the leading strand (31). The substrates for MMR are all six base–base mismatches and 1 to 13-nt insertion/deletion loops (25, 32, 33, 34). Eukaryotic MMR commences with recognition of the mismatch by MutSα or MutSβ (32, 34, 35, 36). MutSα is the primary mismatch-recognition factor that recognizes both base–base mismatches and small insertion/deletion loops whereas MutSβ recognizes small insertion/deletion loops (32, 34, 35, 36, 37). After recognizing the mismatch, MutSα or MutSβ cooperates with RFC-loaded PCNA to activate MutLα endonuclease (38, 39, 40, 41, 42, 43). The activated MutLα endonuclease incises the discontinuous daughter strand 5′ and 3′ to the mismatch. A 5'' strand break formed by MutLα endonuclease is utilized by EXO1 to enter the DNA and excise a discontinuous strand portion encompassing the mismatch in a 5''→3′ excision reaction stimulated by MutSα/MutSβ (38, 44, 45). The generated gap is filled in by the Pol δ holoenzyme, and the nick is ligated by a DNA ligase (44, 46, 47). DNA polymerase ε (Pol ε) can substitute for Pol δ in the EXO1-dependent MMR reaction, but its activity in this reaction is much lower than that of Pol δ (48). Although MutLα endonuclease is essential for MMR in vivo, 5′ nick-dependent MMR reactions reconstituted in the presence of EXO1 are MutLα-independent (44, 47, 49).EXO1 deficiency in humans does not seem to cause significant cancer predisposition (19). Nevertheless, it is known that Exo1^-/- mice are susceptible to the development of lymphomas (50). Genetic studies in yeast and mice demonstrated that EXO1 inactivation causes only a modest defect in MMR (50, 51, 52, 53). In agreement with these genetic studies, a defined human EXO1-independent MMR reaction that depends on the strand-displacement DNA synthesis activity of Pol δ holoenzyme to remove the mismatch was reconstituted (54). Furthermore, an EXO1-independent MMR reaction that occurred in a mammalian cell extract system without the formation of a gapped excision intermediate was observed (54). Together, these findings implicated the strand-displacement activity of Pol δ holoenzyme in EXO1-independent MMR.In this study, we investigated DNA2 in the context of MMR. DNA2 is an essential multifunctional protein that has nuclease, ATPase, and 5''→3′ helicase activities (55, 56, 57). Previous research ascertained that DNA2 removes long flaps during Okazaki fragment maturation (58, 59, 60), participates in the resection step of double-strand break repair (61, 62, 63), initiates the replication checkpoint (64), and suppresses the expansions of GAA repeats (65). We have found in vivo and in vitro evidence that DNA2 promotes EXO1-independent MMR. Our data have indicated that the nuclease activity of DNA2 enhances the strand-displacement activity of Pol δ holoenzyme in an EXO1-independent MMR reaction.     

Wnt Signaling in Vertebrate Axis Specification

The Wnt pathway is a major embryonic signaling pathway that controls cell proliferation, cell fate, and body-axis determination in vertebrate embryos. Soon after egg fertilization, Wnt pathway components play a role in microtubule-dependent dorsoventral axis specification. Later in embryogenesis, another conserved function of the pathway is to specify the anteroposterior axis. The dual role of Wnt signaling in Xenopus and zebrafish embryos is regulated at different developmental stages by distinct sets of Wnt target genes. This review highlights recent progress in the discrimination of different signaling branches and the identification of specific pathway targets during vertebrate axial development.Wnt pathways play major roles in cell-fate specification, proliferation and differentiation, cell polarity, and morphogenesis (Clevers 2006; van Amerongen and Nusse 2009). Signaling is initiated in the responding cell by the interaction of Wnt ligands with different receptors and coreceptors, including Frizzled, LRP5/6, ROR1/2, RYK, PTK7, and proteoglycans (Angers and Moon 2009; Kikuchi et al. 2009; MacDonald et al. 2009). Receptor activation is accompanied by the phosphorylation of Dishev-elled (Yanagawa et al. 1995), which appears to transduce the signal to both the cell membrane and the nucleus (Cliffe et al. 2003; Itoh et al. 2005; Bilic et al. 2007). Another common pathway component is β-catenin, an abundant component of adherens junctions (Nelson and Nusse 2004; Grigoryan et al. 2008). In response to signaling, β-catenin associates with T-cell factors (TCFs) and translocates to the nucleus to stimulate Wnt target gene expression (Behrens et al. 1996; Huber et al. 1996; Molenaar et al. 1996).This β-catenin-dependent activation of specific genes is often referred to as the “canonical” pathway. In the absence of Wnt signaling, β-catenin is destroyed by the protein complex that includes Axin, GSK3, and the tumor suppressor APC (Clevers 2006; MacDonald et al. 2009). Wnt proteins, such as Wnt1, Wnt3, and Wnt8, stimulate Frizzled and LRP5/6 receptors to inactivate this β-catenin destruction complex, and, at the same time, trigger the phosphorylation of TCF proteins by homeodomain-interacting protein kinase 2 (HIPK2) (Hikasa et al. 2010; Hikasa and Sokol 2011). Both β-catenin stabilization and the regulation of TCF protein function by phosphorylation appear to represent general strategies that are conserved in multiple systems (Sokol 2011). Thus, the signaling pathway consists of two branches that together regulate target gene expression (Fig. 1).Open in a separate windowFigure 1.Conserved Wnt pathway branches and components. In the absence of Wnt signals, glycogen synthase kinase 3 (GSK3) binds Axin and APC to form the β-catenin destruction complex. Some Wnt proteins, such as Wnt8 and Wnt3a, stimulate Frizzled and LRP5/6 receptors to inhibit GSK3 activity and stabilize β-catenin (β-cat). Stabilized β-cat forms a complex with T-cell factors (e.g., TCF1/LEF1) to activate target genes. Moreover, GSK3 inhibition leads to target gene derepression by promoting TCF3 phosphorylation by homeodomain-interacting protein kinase 2 (HIPK2) through an unknown mechanism, for which β-catenin is required as a scaffold. This phosphorylation results in TCF3 removal from target promoters and gene activation. Other Wnt proteins, such as Wnt5a and Wnt11, use distinct receptors such as ROR2 and RYK, in addition to Frizzled, to control the the cytoskeletal organization through core planar cell polarity (PCP) proteins, small GTPases (Rho/Rac/Cdc42), and c-Jun amino-terminal kinase (JNK).Other Wnt proteins, such as Wnt5a or Wnt11, strongly affect the cytoskeletal organization and morphogenesis without stabilizing β-catenin (Torres et al. 1996; Angers and Moon 2009; Wu and Mlodzik 2009). These “noncanonical” ligands do not influence TCF3 phosphorylation (Hikasa and Sokol 2011), but may use distinct receptors such as ROR1/2 and RYK instead of or in addition to Frizzled (Hikasa et al. 2002; Lu et al. 2004; Mikels and Nusse 2006; Nishita et al. 2006, 2010; Schambony and Wedlich 2007; Grumolato et al. 2010; Lin et al. 2010; Gao et al. 2011). In such cases, signaling mechanisms are likely to include planar cell polarity (PCP) components, such as Vangl2, Flamingo, Prickle, Diversin, Rho GTPases, and c-Jun amino-terminal kinases (JNKs), which do not directly affect β-catenin stability (Fig. 1) (Sokol 2000; Schwarz-Romond et al. 2002; Schambony and Wedlich 2007; Komiya and Habas 2008; Axelrod 2009; Itoh et al. 2009; Tada and Kai 2009; Sato et al. 2010; Gao et al. 2011). This simplistic dichotomy of the Wnt pathway does not preclude some Wnt ligands from using both β-catenin-dependent and -independent routes in a context-specific manner.Despite the existence of many pathway branches, only the β-catenin-dependent branch has been implicated in body-axis specification. Recent experiments in lower vertebrates have identified additional pathway components and targets and provided new insights into the underlying mechanisms.     

Sexual Conflict between Parents: Offspring Desertion and Asymmetrical Parental Care

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

Comparison of Gas Chromatography and Mineralization Experiments for Measuring Loss of Selected Polychlorinated Biphenyl Congeners in Cultures of White Rot Fungi

Two methods were used to compare the biodegradation of six polychlorinated biphenyl (PCB) congeners by 12 white rot fungi. Four fungi were found to be more active than Phanerochaete chrysosporium ATCC 24725. Biodegradation of the following congeners was monitored by gas chromatography: 2,3-dichlorobiphenyl, 4,4′-dichlorobiphenyl, 2,4′,5-trichlorobiphenyl (2,4′,5-TCB), 2,2′,4,4′-tetrachlorobiphenyl, 2,2′,5,5′-tetrachlorobiphenyl, and 2,2′,4,4′,5,5′-hexachlorobiphenyl. The congener tested for mineralization was 2,4′,5-[U-¹⁴C]TCB. Culture supernatants were also assayed for lignin peroxidase and manganese peroxidase activities. Of the fungi tested, two strains of Bjerkandera adusta (UAMH 8258 and UAMH 7308), one strain of Pleurotus ostreatus (UAMH 7964), and Trametes versicolor UAMH 8272 gave the highest biodegradation and mineralization. P. chrysosporium ATCC 24725, a strain frequently used in studies of PCB degradation, gave the lowest mineralization and biodegradation activities of the 12 fungi reported here. Low but detectable levels of lignin peroxidase and manganese peroxidase activity were present in culture supernatants, but no correlation was observed among any combination of PCB congener biodegradation, mineralization, and lignin peroxidase or manganese peroxidase activity. With the exception of P. chrysosporium, congener loss ranged from 40 to 96%; however, these values varied due to nonspecific congener binding to fungal biomass and glassware. Mineralization was much lower, ≤11%, because it measures a complete oxidation of at least part of the congener molecule but the results were more consistent and therefore more reliable in assessment of PCB biodegradation.

Polychlorinated biphenyls (PCBs) are produced by chlorination of biphenyl, resulting in up to 209 different congeners. Commercial mixtures range from light oily fluids to waxes, and their physical properties make them useful as heat transfer fluids, hydraulic fluids, solvent extenders, plasticizers, flame retardants, organic diluents, and dielectric fluids (1, 21). Approximately 24 million lb are in the North American environment (19). The stability and hydrophobic nature of these compounds make them a persistent environmental hazard.To date, bacterial transformations have been the main focus of PCB degradation research. Aerobic bacteria use a biphenyl-induced dioxygenase enzyme system to attack less-chlorinated congeners (mono- to hexachlorobiphenyls) (1, 5, 7, 8, 22). Although more-chlorinated congeners are recalcitrant to aerobic bacterial degradation, microorganisms in anaerobic river sediments reductively dechlorinate these compounds, mainly removing the meta and para chlorines (1, 6, 10, 33, 34).The degradation of PCBs by white rot fungi has been known since 1985 (11, 18). Many fungi have been tested for their ability to degrade PCBs, including the white rot fungi Coriolus versicolor (18), Coriolopsis polysona (41), Funalia gallica (18), Hirneola nigricans (35), Lentinus edodes (35), Phanerochaete chrysosporium (3, 11, 14, 17, 18, 35, 39, 41–43), Phlebia brevispora (18), Pleurotus ostreatus (35, 43), Poria cinerescens (18), Px strain (possibly Lentinus tigrinus) (35), and Trametes versicolor (41, 43). There have also been studies of PCB metabolism by ectomycorrhizal fungi (17) and other fungi such as Aspergillus flavus (32), Aspergillus niger (15), Aureobasidium pullulans (18), Candida boidinii (35), Candida lipolytica (35), Cunninghamella elegans (16), and Saccharomyces cerevisiae (18, 38). The mechanism of PCB biodegradation has not been definitively determined for any fungi. White rot fungi produce several nonspecific extracellular enzymes which have been the subject of extensive research. These nonspecific peroxidases are normally involved in lignin degradation but can oxidize a wide range of aromatic compounds including polycyclic aromatic hydrocarbons (37). Two peroxidases, lignin peroxidase (LiP) and Mn peroxidase (MnP), are secreted into the environment of the fungus under conditions of nitrogen limitation in P. chrysosporium (23, 25, 27, 29) but are not stress related in fungi such as Bjerkandera adusta or T. versicolor (12, 30).Two approaches have been used to determine the biodegradability of PCBs by fungi: (i) loss of the parent congener analyzed by gas chromatography (GC) (17, 32, 35, 42, 43) and (ii) mineralization experiments in which the ¹⁴C of the universally labeled ¹⁴C parent congener is recovered as ¹⁴CO₂ (11, 14, 18, 39, 41). In the first method, the loss of a peak on a chromatogram makes it difficult to decide whether the PCB is being partly degraded, mineralized, adsorbed to the fungal biomass, or bound to glassware, soil particles, or wood chips. Even when experiments with killed-cell and abiotic controls are performed, the extraction efficiency and standard error can make data difficult to interpret. For example, recoveries can range anywhere from 40 to 100% depending on the congener used and the fungus being investigated (17). On the other hand, recovery of significant amounts of ¹⁴CO₂ from the cultures incubated with a ¹⁴C substrate provides definitive proof of fungal metabolism. There appears to be only one report relating data from these two techniques (18), and in that study, [U-¹⁴C]Aroclor 1254, rather than an individual congener, was used.In this study, we examined the ability of 12 white rot fungal strains to metabolize selected PCB congeners to determine which strains were the most active degraders. Included in this group was P. chrysosporium ATCC 24725, a strain used extensively in PCB studies (3, 14, 18, 35, 39, 41–43). Six PCB congeners were selected to give a range of chlorine substitutions and therefore a range of potential biodegradability which was monitored by GC. One of the chosen congeners was ¹⁴C labeled and used in studies to compare the results from a mineralization method with those from the GC method.     

Direct-Imaging-Based Quantification of Bacillus cereus ATCC 14579 Population Heterogeneity at a Low Incubation Temperature

Bacillus cereus ATCC 14579 was cultured in microcolonies on Anopore strips near its minimum growth temperature to directly image and quantify its population heterogeneity at an abusive refrigeration temperature. Eleven percent of the microcolonies failed to grow during low-temperature incubation, and this cold-induced population heterogeneity could be partly attributed to the loss of membrane integrity of individual cells.Bacillus cereus is a food poisoning- and food spoilage-causing organism that can be found in a large variety of foods (4, 23). There are two illnesses associated with B. cereus, namely, emetic and diarrheal intoxication (17, 24). Most of the strains related to cases or outbreaks of B. cereus food-borne poisoning were shown to be unable to grow at 7°C (1, 12). The average temperatures of domestic refrigerators have been investigated in various surveys around the world and often ranged from 5°C to 7°C, but extreme values exceeded 10°C to 12°C (5, 16). Inadequate chilling was indeed reported in various incidents of B. cereus food-borne illness (7, 8, 18, 19), pointing to the importance of appropriate refrigeration of foods contaminated with B. cereus to control its growth and toxin production in foods (9).Several studies have demonstrated that microorganisms can show diversity in their population stress response, even in an apparently homogeneous stress environment (6, 11, 21, 22). However, only very limited data describing the heterogeneity in growth performance of individual cells from food-borne pathogens cultured at low temperatures are available (10). Because inadequate chilling of food is one of the factors that contribute to the number of incidents of B. cereus food-borne illness, there is a need for better understanding of its growth performance at lowered incubation temperatures. In this study, we used the direct-imaging-based Anopore technology (6, 13-15) to quantitatively describe the population heterogeneity of B. cereus ATCC 14579 cells at 12°C. The minimum temperature for the growth of B. cereus ATCC 14579 in brain heart infusion (BHI) broth is 7.5°C (personal communication from F. Carlin), but various food-borne-associated B. cereus isolates were shown to be unable to grow at 10°C (1). Therefore, in this study, a culturing temperature of 12°C was chosen, to mimic temperature abuse of refrigerated foods. In addition, the membrane integrity of individual cells was assessed using both membrane permeant and impermeant nucleic acid dyes in order to get more insight into cellular characteristics that may contribute to heterogeneity in growth response.     

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.