Crystal Structures of the ATPase Domains of Four Human Hsp70 Isoforms: HSPA1L/Hsp70-hom,HSPA2/Hsp70-2, HSPA6/Hsp70B', and HSPA5/BiP/GRP78

The 70-kDa heat shock proteins (Hsp70) are chaperones with central roles in processes that involve polypeptide remodeling events. Hsp70 proteins consist of two major functional domains: an N-terminal nucleotide binding domain (NBD) with ATPase activity, and a C-terminal substrate binding domain (SBD). We present the first crystal structures of four human Hsp70 isoforms, those of the NBDs of HSPA1L, HSPA2, HSPA5 and HSPA6. As previously with Hsp70 family members, all four proteins crystallized in a closed cleft conformation, although a slight cleft opening through rotation of subdomain IIB was observed for the HSPA5-ADP complex. The structures presented here support the view that the NBDs of human Hsp70 function by conserved mechanisms and contribute little to isoform specificity, which instead is brought about by the SBDs and by accessory proteins.

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Crystal Structure of the ATPase Domain of the Human AAA+ Protein Paraplegin/SPG7

Paraplegin is an m-AAA protease of the mitochondrial inner membrane that is linked to hereditary spastic paraplegias. The gene encodes an FtsH-homology protease domain in tandem with an AAA+ homology ATPase domain. The protein is believed to form a hexamer that uses ATPase-driven conformational changes in its AAA-domain to deliver substrate peptides to its protease domain. We present the crystal structure of the AAA-domain of human paraplegin bound to ADP at 2.2 Å. This enables assignment of the roles of specific side chains within the catalytic cycle, and provides the structural basis for understanding the mechanism of disease mutations.

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Structure of the CaMKIIδ/Calmodulin Complex Reveals the Molecular Mechanism of CaMKII Kinase Activation

Long-term potentiation (LTP), a long-lasting enhancement in communication between neurons, is considered to be the major cellular mechanism underlying learning and memory. LTP triggers high-frequency calcium pulses that result in the activation of Calcium/Calmodulin (CaM)-dependent kinase II (CaMKII). CaMKII acts as a molecular switch because it remains active for a long time after the return to basal calcium levels, which is a unique property required for CaMKII function. Here we describe the crystal structure of the human CaMKIIδ/Ca²⁺/CaM complex, structures of all four human CaMKII catalytic domains in their autoinhibited states, as well as structures of human CaMKII oligomerization domains in their tetradecameric and physiological dodecameric states. All four autoinhibited human CaMKIIs were monomeric in the determined crystal structures but associated weakly in solution. In the CaMKIIδ/Ca²⁺/CaM complex, the inhibitory region adopted an extended conformation and interacted with an adjacent catalytic domain positioning T287 into the active site of the interacting protomer. Comparisons with autoinhibited CaMKII structures showed that binding of calmodulin leads to the rearrangement of residues in the active site to a conformation suitable for ATP binding and to the closure of the binding groove for the autoinhibitory helix by helix αD. The structural data, together with biophysical interaction studies, reveals the mechanism of CaMKII activation by calmodulin and explains many of the unique regulatory properties of these two essential signaling molecules.

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Crystal Structure of the PIM2 Kinase in Complex with an Organoruthenium Inhibitor

Background

The serine/threonine kinase PIM2 is highly expressed in human leukemia and lymphomas and has been shown to positively regulate survival and proliferation of tumor cells. Its diverse ATP site makes PIM2 a promising target for the development of anticancer agents. To date our knowledge of catalytic domain structures of the PIM kinase family is limited to PIM1 which has been extensively studied and which shares about 50% sequence identity with PIM2.

Principal Findings

Here we determined the crystal structure of PIM2 in complex with an organoruthenium complex (inhibition in sub-nanomolar level). Due to its extraordinary shape complementarity this stable organometallic compound is a highly potent inhibitor of PIM kinases.

Significance

The structure of PIM2 revealed several differences to PIM1 which may be explored further to generate isoform selective inhibitors. It has also demonstrated how an organometallic inhibitor can be adapted to the binding site of protein kinases to generate highly potent inhibitors.

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Structural Basis for Substrate Specificity in Human Monomeric Carbonyl Reductases

Carbonyl reduction constitutes a phase I reaction for many xenobiotics and is carried out in mammals mainly by members of two protein families, namely aldo-keto reductases and short-chain dehydrogenases/reductases. In addition to their capacity to reduce xenobiotics, several of the enzymes act on endogenous compounds such as steroids or eicosanoids. One of the major carbonyl reducing enzymes found in humans is carbonyl reductase 1 (CBR1) with a very broad substrate spectrum. A paralog, carbonyl reductase 3 (CBR3) has about 70% sequence identity and has not been sufficiently characterized to date. Screening of a focused xenobiotic compound library revealed that CBR3 has narrower substrate specificity and acts on several orthoquinones, as well as isatin or the anticancer drug oracin. To further investigate structure-activity relationships between these enzymes we crystallized CBR3, performed substrate docking, site-directed mutagenesis and compared its kinetic features to CBR1. Despite high sequence similarities, the active sites differ in shape and surface properties. The data reveal that the differences in substrate specificity are largely due to a short segment of a substrate binding loop comprising critical residues Trp229/Pro230, Ala235/Asp236 as well as part of the active site formed by Met141/Gln142 in CBR1 and CBR3, respectively. The data suggest a minor role in xenobiotic metabolism for CBR3.

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Structural Comparison of Human Mammalian Ste20-Like Kinases

Background

The serine/threonine mammalian Ste-20 like kinases (MSTs) are key regulators of apoptosis, cellular proliferation as well as polarization. Deregulation of MSTs has been associated with disease progression in prostate and colorectal cancer. The four human MSTs are regulated differently by C-terminal regions flanking the catalytic domains.

Principal Findings

We have determined the crystal structure of kinase domain of MST4 in complex with an ATP-mimetic inhibitor. This is the first structure of an inactive conformation of a member of the MST kinase family. Comparison with active structures of MST3 and MST1 revealed a dimeric association of MST4 suggesting an activation loop exchanged mechanism of MST4 auto-activation. Together with a homology model of MST2 we provide a comparative analysis of the kinase domains for all four members of the human MST family.

Significance

The comparative analysis identified new structural features in the MST ATP binding pocket and has also defined the mechanism for autophosphorylation. Both structural features may be further explored for inhibitors design.

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Comparative structural analysis of lipid binding START domains

Background

Steroidogenic acute regulatory (StAR) protein related lipid transfer (START) domains are small globular modules that form a cavity where lipids and lipid hormones bind. These domains can transport ligands to facilitate lipid exchange between biological membranes, and they have been postulated to modulate the activity of other domains of the protein in response to ligand binding. More than a dozen human genes encode START domains, and several of them are implicated in a disease.

Principal Findings

We report crystal structures of the human STARD1, STARD5, STARD13 and STARD14 lipid transfer domains. These represent four of the six functional classes of START domains.

Significance

Sequence alignments based on these and previously reported crystal structures define the structural determinants of human START domains, both those related to structural framework and those involved in ligand specificity.

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Collection Overview: Ten Years of Wonderful Open Access Science

To mark our tenth Anniversary at PLOS Biology, we are launching a special, celebratory Tenth Anniversary PLOS Biology Collection which showcases 10 specially selected PLOS Biology research articles drawn from a decade of publishing excellent science. It also features newly commissioned articles, including thought-provoking pieces on the Open Access movement (past and present), on article-level metrics, and on the history of the Public Library of Science. Each research article highlighted in the collection is also accompanied by a PLOS Biologue blog post to extend the impact of these remarkable studies to the widest possible audience.As we celebrate 10 years of PLOS Biology, 10 years of the Public Library of Science, and 10 years of strong advocacy and trail-blazing for the Open Access movement, we mustn''t forget the real star of the show – the fantastic science that we''ve published.It''s hard to cast one''s mind back 10 years and recall the scepticism with which open access publishing was initially received. A key concern at the time was that the model would be tainted with the stigma of “vanity publishing,” and that this model, in which the author pays to publish, is incompatible with integrity, editorial rigour, and scientific excellence. As also discussed in the accompanying editorial [1], the sheer quality of the science that has appeared in PLOS Biology has been vital for dispelling this myth.Our tenth anniversary provides us with a great opportunity to celebrate all of the 1800 or so research articles published in PLOS Biology since our launch in 2003. Unable to showcase each one in turn, we turned to our Editorial Board to help us pick the top 10 research articles to feature in a special Tenth Anniversary PLOS Biology Collection (www.ploscollections.org/Biology10thAnniversary). During the month of October, we will also publish a PLOS Biologue blog post (http://blogs.plos.org/biologue/) for each of these selected research articles, trying to capture and convey what it is about them that the staff editors, the editorial board, and the authors feel is special.By now, you''re probably wondering which papers we selected. The selection is detailed in Box 1, with links to each article. If you haven''t read these articles before, we urge you to read them now and to judge for yourself. As Editorial Board Member Steve O''Rahilly put it, “I think a common theme in many of the best PLOS Biology papers is that they are rich in data that is analysed very carefully and self-critically and presented without hype. However the conclusions are important for the biological community and their insights are likely to stand the test of time.”As well as publishing research articles, PLOS Biology has a thriving Magazine section that has hosted scientific and policy debates, aired polemical and provocative views, celebrated scientific lives in obituaries, reviewed interesting books, and explored unsolved mysteries. One example of how this section has triggered productive community debate is Rosie Redfield''s Perspective on how genetics should be taught to undergraduates [2]. Yet we don''t seek just to provoke debate, but also to enlighten; take a moment to read Georgina Mace''s editorial on the current issues and debates in the sustainability sciences [3]. We also try to break down barriers between fields [4] and to promote public engagement with science [5],[6].We feel strongly that our role doesn''t end with publishing the research article itself. Instead, we aim to unpackage the fascinating discoveries published in PLOS Biology by commissioning articles that explain the significance and impact of the research we publish to audiences of varying expertise. These companion articles range from Primers, which are written by experts who contextualise research articles for those in the field; to Synopses, which are written by science writers who digest an article for our wider readership of biologists; and finally, to PLOS Biologue blog posts, which distil research discoveries for a more general scientifically engaged public. We also use social media to bring these findings to the attention of a global online audience.Of course, the continued success of PLOS Biology doesn''t rest solely on the amazing research we''ve already published; it also hinges on the ground-breaking science we strive to publish in the future. Maintaining the high quality of the biology that we publish is of vital importance to us, not least because, as Editorial Board Member Robert Insall reflects, “What I like about PLOS Biology is that it avoids other journals'' fixation on fashion and the biggest names. This means the papers PLOS Biology is publishing now will last longer and mean more in a generation''s time.”

Box 1. Research Articles Featured in the Tenth Anniversary PLOS Biology Collection

Our Editorial Board Members helped us select 10 articles from the great science published during PLOS Biology''s first decade to feature in our Tenth Anniversary Collection. Please access these articles from the list below and from our Collection page. To read the PLOS Biologue blog posts that accompany them, please go to http://blogs.plos.org/biologue/ for more information.Carmena J et al. (2003) Learning to Control a BrainMachine Interface for Reaching and Grasping by Primates  Primer: Current Approaches to the Study of Movement Control  Synopsis: Retraining the Brain to Recover Movement Brennecke J et al. (2004) Principles of MicroRNA–Target Recognition  Synopsis: Seeds of Destruction: Predicting How microRNAs Choose Their Target Voight BF et al. (2005) A Map of Recent Positive Selection in the Human Genome  Synopsis: Clues to Our Past: Mining the Human Genome for Signs of Recent Selection Palmer C et al. (2007) Development of the Human Infant Intestinal Microbiota  Synopsis: Microbes Colonize a Baby''s Gut with Distinction Levy S et al. (2007) The Diploid Genome Sequence of an Individual Human  Synopsis: A New Human Genome Sequence Paves the Way for Individualized Genomics Illingworth R et al. (2008) A Novel CpG Island Set Identifies Tissue-Specific Methylation at Developmental Gene Loci Silva J et al. (2008) Promotion of Reprogramming to Ground State Pluripotency by Signal Inhibition  Synopsis: A Shortcut to Immortality: Rapid Reprogramming with Tissue Cells Coppé J-P et al. (2008) Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor Shu X et al. (2011) A Genetically Encoded Tag for Correlated Light and Electron Microscopy of Intact Cells, Tissues, and Organisms Bonds MH et al. (2012) Disease Ecology, Biodiversity, and the Latitudinal Gradient in Income  Synopsis: Which Came First: Burden of Infectious Disease or Poverty?     

Characterizing the Transmission Dynamics and Control of Ebola Virus Disease

Carefully calibrated transmission models have the potential to guide public health officials on the nature and scale of the interventions required to control epidemics. In the context of the ongoing Ebola virus disease (EVD) epidemic in Liberia, Drake and colleagues, in this issue of PLOS Biology, employed an elegant modeling approach to capture the distributions of the number of secondary cases that arise in the community and health care settings in the context of changing population behaviors and increasing hospital capacity. Their findings underscore the role of increasing the rate of safe burials and the fractions of infectious individuals who seek hospitalization together with hospital capacity to achieve epidemic control. However, further modeling efforts of EVD transmission and control in West Africa should utilize the spatial-temporal patterns of spread in the region by incorporating spatial heterogeneity in the transmission process. Detailed datasets are urgently needed to characterize temporal changes in population behaviors, contact networks at different spatial scales, population mobility patterns, adherence to infection control measures in hospital settings, and hospitalization and reporting rates.Ebola virus disease (EVD) is caused by an RNA virus of the family Filoviridae and genus Ebolavirus. Five different Ebolavirus strains have been identified, namely Zaire ebolavirus (EBOV), Sudan ebolavirus (SUDV), Tai Forest ebolavirus (TAFV), Bundibugyo ebolavirus (BDBV), and Reston ebolavirus (RESTV). The great majority of past Ebola outbreaks in humans have been linked to three Ebola strains: EBOV, SUDV, and BDBV [1]. The Ebola virus ([EBOV] formerly designated Zaire ebolavirus) derived its name from the Ebola River, located near the epicenter of the first outbreak identified in 1976 in Zaire (now the Democratic Republic of Congo). EVD outbreaks among humans have been associated with direct human exposure to fruit bats—the most likely reservoir of the virus—or through contact with intermediate infected hosts, which include gorillas, chimpanzees, and monkeys. Outbreaks have been reported on average every 1.5 years [2]. Past EVD outbreaks have occurred in relatively isolated areas and have been limited in size and duration (Fig. 1). It has been recently estimated that about 22 million people living in areas of Central and West Africa are at risk of EVD [3].Open in a separate windowFigure 1Time series of the temporal progression of four past EVD outbreaks in Congo (1976, 1995, 2014) [4–6] and Uganda (2000) [7].An epidemic of EVD (EBOV) has been spreading in West Africa since December 2013 in Guinea, Liberia, and Sierra Leone [8]. A total of 18,603 cases, with 6,915 deaths, have been reported to the World Health Organization as of December 17, 2014 [9]. While the causative strain associated with this epidemic is closely related to that of past outbreaks in Central Africa [10], three key factors have contributed disproportionately to this unprecedented epidemic: (1) substantial delays in detection and implementation of control efforts in a region characterized by porous borders; (2) limited public health infrastructure including epidemiological surveillance systems and diagnostic testing [11], which are necessary for the timely diagnosis of symptomatic individuals, effective isolation of infectious individuals, contact tracing to rapidly identify new cases, and providing supportive care to increase the chances of survival to EVD infection; and (3) cultural practices that involve touching the body of the deceased and the association of illness with witchcraft or conspiracy theories.EBOV is transmitted by direct human-to-human contact via body fluids or indirect contact with contaminated surfaces, but it is not spread through the airborne route. Individuals become symptomatic after an average incubation period of 10 days (range 2–21 days) [12], and infectiousness is increased during the later stages of disease [13]. The characteristic symptoms of EVD are nonspecific and include sudden onset of fever, weakness, vomiting, diarrhea, headache, and a sore throat, while only a fraction of the symptomatic individuals present with hemorrhagic manifestations [14]. The case fatality risk (CFR), calculated as the proportion of deaths among the total number of EVD cases with known outcomes, has been estimated from data of the first 9 months of the epidemic in West Africa at 70.8% (95% CI 68.6–72.8), in broad agreement with estimates from past outbreaks [12].Two important quantities to understand in the transmission dynamics of EVD are the serial interval and the basic reproduction number. The serial interval is defined as the time from illness onset in a primary case to illness onset in a secondary case [15] and has been estimated at 15 days on average for the ongoing epidemic [12]. The basic reproduction number, R ₀, quantifies transmission potential at the beginning of an epidemic and is defined as the average number of secondary cases generated by a typical infected individual during the early phase of an epidemic, before interventions are put in place [16]. If R ₀ < 1, transmission is not sufficient to generate a major epidemic. In contrast, a major epidemic is likely to occur whenever R ₀ > 1. When transmission potential is measured over time t, the effective reproduction number R_t, can be helpful to quantify the time-dependent transmission potential resulting from the effect of control interventions and behavior changes [17]. Estimates of R ₀ for the ongoing epidemic in West Africa have fluctuated around 2 with some uncertainty (e.g., [12, 18–22]), which are in good agreement with estimates from past EVD outbreaks [23]. R ₀ could also vary across regions as a function of the local public health infrastructure (e.g., availability of health care settings and infection control protocols), such that an outbreak may be very unlikely to unfold in developed countries simply as a result of baseline infection control measures in place (i.e., R ₀ < 1) while poor countries with extremely weak or absent public health systems may be unable to control an Ebola outbreak (i.e., R ₀ > 1).Mathematical models of disease transmission have proved to be useful tools to characterize the transmission dynamics of infectious diseases and evaluate the effects of control intervention strategies in order to inform public health policy [16, 24, 25]. There are a limited number of mathematical models for the transmission and control of EVD, but a number of efforts are underway in the context of the epidemic in West Africa. The transmission dynamics of EVD have been modeled on the basis of the simple compartmental susceptible-exposed-infectious-removed (SEIR) model that assumes a homogenously mixed population [23]. The modeled population can be structured according to the contributions of community, hospital, and unsafe burials to transmission as EVD transmission has been amplified in health care settings with ineffective infection control measures and during unsafe burials [23]. A schematic representation of the main transmission pathways of EVD is shown in Fig. 2.Open in a separate windowFigure 2Schematic representation of the transmission dynamics of Ebola virus disease.A recent study published in PLOS Biology by Drake and colleagues [26] presents an interesting and flexible modeling framework for the transmission and control of EVD in Liberia. Their framework is based on a multi-type branching process model in which “multi-type” refers to the consideration of two types of settings where transmission can occur, while “branching process” is the mathematical term to specify a probabilistic model. For instance, in the case of a single-type branching process, the transmission dynamics are simply described using a single reproduction number, i.e., the average number of secondary cases produced by a single primary case. However, when two types of hosts are considered in the transmission process, two reproduction numbers are needed to characterize within-group mixing (e.g., within-hospital and within-community transmission) and two reproduction numbers characterize transmission between groups (e.g., transmission from hospital to community and vice versa).Drake and colleague’s elegant modeling approach describes EVD transmission according to infection generations by calculating probability distributions of the number of secondary cases that arise in the community via nursing care or during unsafe burials and in health care settings via infections to health care workers and visitors. The model explicitly accounts for the hospitalization rate—the fraction of infectious individuals in the community seeking hospitalization (estimated in this study at 60%). However, the number of effectively isolated infectious individuals is constrained by the number of available beds in treatment centers—which are assumed in this study to operate at twice their regular capacity. It is important to note that the number of beds available to treat EVD patients was severely limited in Liberia prior to mid August 2014 (Fig. 1 in [26]). Moreover, the rate of safe burials that reduces the force of infection is included in their model as an increasing function of time. The model was calibrated by tuning six parameters to fit the trajectories of the number of reported cases in the community and among health care workers during the period 4 July to 2 September 2014 for a total of four infection generations during which the effective reproduction number was estimated to decline on average from about 2.8 to 1.4. The model was able to effectively capture heterogeneity in transmission of EVD in both the community and hospital settings.Drake and colleagues [26] employed their calibrated model to forecast the epidemic trajectory in Liberia from 3 September to 31 December 2014 under different scenarios that account for an increasing fraction of cases seeking hospitalization and a surge in the number of beds available to isolate and treat EVD patients. Their results indicate that allocating 1,700 additional beds (100 new beds every 4 days) in new Ebola treatment centers committed by US aid reduces the mean epidemic size to ~51,000 (60% reduction with respect to the baseline scenario), while epidemic control by mid-March is only plausible through a 4-fold increase in the number of beds committed by US aid and enhancing the hospitalization rate from 60% to 99% for a final epidemic size of 12,285. Moreover, an additional epidemic forecast incorporating data up to 1 December 2014 indicated that containment could be achieved between March and June 2015.Other interventions were not explicitly incorporated in their model because it is difficult to parameterize them in the absence of datasets that permit statistical estimation of their impact on the transmission dynamics. These additional interventions include the use of household protection kits, designed to reduce transmission in the community; improvements in infection control protocols in health care settings that reduce transmission among health care workers; and the impact of rapid diagnostic kits in Ebola treatment centers, which reduce the time to isolation for infectious individuals seeking hospitalization. Increasing awareness and education of the population about the disease could have also yielded further reductions in case incidence by reducing the size of the at-risk susceptible population (Fig. 3) [27]. Nevertheless, some of these effects could have been indirectly captured implicitly by the time-dependent safe burial rate parameter in their model.Open in a separate windowFigure 3Contrasting epidemic growth in the presence and absence of behavior changes that reduce the transmission rate.Importantly, prior models of EVD transmission [23, 28, 29] and the model by Drake and colleagues have not incorporated spatial heterogeneity in the transmission dynamics. In particular, the EVD epidemic in West Africa can be characterized as a set of asynchronous local (e.g., district) epidemics that exhibit sub-exponential growth, which could be driven by a highly clustered underlying contact network or population behavior changes induced by the accumulation of morbidity and mortality rates (see Fig. 4 and [30]). EVD contagiousness is most pronounced in the later and more severe stages of Ebola infection when infectious individuals are confined at home or health care settings and mostly exposed to caregivers (e.g., health care workers, family members) [30]. This characterization would lead to EVD transmission over a network of contacts that is highly clustered (e.g., individuals are likely to share a significant fraction of their contacts), which is associated with significantly slower spread relative to the common random mixing assumption as illustrated in Fig. 5. The development of transmission models that incorporate spatial heterogeneity (e.g., by modeling spatial coupling or human migration) is currently limited by the shortage of detailed datasets from the EVD-affected areas about the geographic distribution of households, health care settings, reporting and hospitalization rates across urban and rural areas, and patterns of population mobility in the region. Some of these limitations may be overcome in the near future. For instance, cell phone data could provide a basis to characterize population mobility in the region at a refined spatial scale.Open in a separate windowFigure 4Representative time series of the cumulative number of EVD cases (in log scale) at the district level in Guinea, Sierra Leone, and Liberia.Open in a separate windowFigure 5Epidemic growth in two populations characterized by two different underlying contact networks.The ongoing epidemic in West Africa offers a unique opportunity to improve our current understanding of the transmission characteristics of EVD in humans. To achieve this goal, it is crucial to collect spatial-temporal data on population behaviors, contact networks, social distancing measures, and education campaigns. Datasets comprising detailed demographic, socio-economic, contact rates, and population mobility estimates in the region (e.g., commuting networks, air traffic) need to be integrated and made publicly available in order to develop highly resolved transmission models, which could guide control strategies with greater precision in the context of the EVD epidemic in West Africa. Although recent data from Liberia indicates that the epidemic is on track for eventual control, the epidemic in Sierra Leone continues an increasing trend, and in Guinea, case incidence roughly follows a steady trend. The potential impact of vaccines should also be incorporated in future modeling efforts as these pharmaceutical interventions are expected to become available in the upcoming months.     

Crystal Structure of the N-Acetylmannosamine Kinase Domain of GNE

Background

UDP-GlcNAc 2-epimerase/ManNAc 6-kinase, GNE, is a bi-functional enzyme that plays a key role in sialic acid biosynthesis. Mutations of the GNE protein cause sialurea or autosomal recessive inclusion body myopathy/Nonaka myopathy. GNE is the only human protein that contains a kinase domain belonging to the ROK (repressor, ORF, kinase) family.

Principal Findings

We solved the structure of the GNE kinase domain in the ligand-free state. The protein exists predominantly as a dimer in solution, with small populations of monomer and higher-order oligomer in equilibrium with the dimer. Crystal packing analysis reveals the existence of a crystallographic hexamer, and that the kinase domain dimerizes through the C-lobe subdomain. Mapping of disease-related missense mutations onto the kinase domain structure revealed that the mutation sites could be classified into four different groups based on the location – dimer interface, interlobar helices, protein surface, or within other secondary structural elements.

Conclusions

The crystal structure of the kinase domain of GNE provides a structural basis for understanding disease-causing mutations and a model of hexameric wild type full length enzyme.

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Origin of the Yeast Whole-Genome Duplication

Whole-genome duplications (WGDs) are rare evolutionary events with profound consequences. They double an organism’s genetic content, immediately creating a reproductive barrier between it and its ancestors and providing raw material for the divergence of gene functions between paralogs. Almost all eukaryotic genome sequences bear evidence of ancient WGDs, but the causes of these events and the timing of intermediate steps have been difficult to discern. One of the best-characterized WGDs occurred in the lineage leading to the baker’s yeast Saccharomyces cerevisiae. Marcet-Houben and Gabaldón now show that, rather than simply doubling the DNA of a single ancestor, the yeast WGD likely involved mating between two different ancestral species followed by a doubling of the genome to restore fertility.The unicellular baker’s yeast Saccharomyces cerevisiae was the first eukaryote to have its genome sequenced, using the first generation of automated sequencing machines and before the advent of the whole-genome shotgun approach. The sequencing was done during the period between 1990 and 1996 by an international consortium that included many small European laboratories, one of which was mine. Each laboratory was given a “tranche” of about 30 kb to sequence, and when you had completed that chunk, you could apply for another one. We were paid €2 per base pair. Progress meetings, chaired energetically by André Goffeau [1], were held every six months to ensure that the project remained on track. At these meetings, each group would make a 5-minute presentation about the genes they had found in their current chunk. The presentations were often tedious, enlivened only by the occasional exigency for André to reassign pieces of DNA from the sequencing tortoises to the hares. But as the project progressed, a pattern began to emerge: many of the chunks were similar to other chunks. The first clone that I sequenced happened to contain the centromere of chromosome II, and I noticed that a gene beside it had a paralog beside the centromere of chromosome IV [2]. My second chunk, from chromosome XV, contained four genes that had four paralogs, in the same order, on chromosome I [3].When the complete genome was released in April 1996, we were able to identify 55 large duplicated blocks of this type, ranging in size from three to 18 duplicated genes (Fig 1) [4]. Two observations indicated that the duplications were quite old: the average amino acid sequence identity between the gene pairs was only 63%, and within each block only about 25% of the genes were actually duplicated, the others being single copy. This pattern suggested that the whole block was initially duplicated, and then many individual genes were deleted. Two other observations suggested that the blocks were remnants of duplicated chromosomes that had become rearranged during evolution: there were almost no overlaps between the blocks, and the orientation of each pair of blocks was conserved relative to the centromeres and telomeres. This layout of blocks was consistent with duplication of the whole genome followed by both extensive deletion of single genes and genome rearrangement solely by the process of reciprocal translocation between chromosomes [4]. Under this hypothesis, there had been an ancient whole-genome duplication (WGD), and the 55 blocks that we could identify were simply the most duplicate-dense regions that still survived without evolutionary rearrangement.Open in a separate windowFig 1A simple model of WGD, gene loss, and synteny relationships.The upper panel shows how duplicated blocks were initially identified using only genes that remain in duplicate in S. cerevisiae [4]. The lower panel shows how additional data from non-WGD yeasts such as Lachancea waltii [5] allowed the parts of the genome that were not initially allocated to blocks to be placed into pairs, providing a duplication map that covered the whole S. cerevisiae genome. Letters A–W represent genes, and dots represent centromeres. Only two chromosomes (yellow and brown) are shown.The hypothesis of a WGD in S. cerevisiae was confirmed in 2004 when three groups sequenced the genomes of species that had branched off from this lineage before the WGD occurred [5–7]. These non-WGD genomes had a “double conserved synteny” relationship with the S. cerevisiae genome—that is, instead of each pair of duplicated regions, they had a single region containing all the genes in a merged order (Fig 1). This discovery allowed the entire genome of S. cerevisiae to be mapped into pairs of regions via their double conserved synteny with the non-WGD species, even if the pairs retain no duplicated genes, thus filling the gaps between the initial map of 55 duplicated blocks. These analyses proved that the WGD encompassed the entire genome of S. cerevisiae and showed that its 16 centromeres fall into eight ancestral pairs that are syntenic with centromeres of the non-WGD species. It therefore appeared that the WGD turned an eight-chromosome ancestor into a 16-chromosome descendant. From this complete map, we now know that among the 5,774 protein-coding genes of S. cerevisiae, there are 551 pairs of duplicated genes (ohnologs) that were formed by the WGD and that about 144 chromosomal rearrangements scrambled the genome after the WGD [8,9]. We also know that the WGD is not confined to Saccharomyces but occurred in the common ancestor of six genera, some of which diverged from each at an early stage when more than 4,000 genes were still duplicated, leading to later losses of different gene copies in different lineages [10].What were the molecular events that caused the WGD? It is relatively easy to draw a diagram summarizing the history of each chromosomal region (Fig 2), but it is much more difficult to specify the provenance of the intermediate molecules and the timescales involved. Two alternative scenarios can describe the steps in Fig 2. In both scenarios, event 1 is a DNA replication, and cells W and Z are each capable of mating (they are respectively a non-WGD haploid and a post-WGD haploid). The key question is whether the DNA molecules labeled X and Y existed in (1) two different cells of the same species or (2) two cells of two different species. Scenario 1 is called autopolyploidization, in which case event 1 corresponds to a simple cell division and event 2 is a mating between gametes from the same species or some other form of cell fusion. Scenario 2 is called allopolyploidization or hybridization, in which case event 1 is a speciation and event 2 is an interspecies mating or cell fusion. If event 2 was a mating, then an additional step such as deletion of one allele at the MAT locus is necessary to convert cell Z from a nonmating zygote to a mating gamete—but it is not essential that this additional step occurred immediately after event 2. In fact, a long delay in which cell Z replicated mitotically for many generations could be useful because it could allow reproductive isolation from cells of type W to build up. Eventually (event 3), mating between two post-WGD haploid cells of type Z can produce a post-WGD diploid like cell ZZ, which is the state in which S. cerevisiae is normally found in nature.Open in a separate windowFig 2Tracing the history of a single chromosomal region.See text for details. In an allopolyploidization, the red and blue chromosomes are called homeologs.The major difference between these two scenarios is the amount of time (T) that elapsed between events 1 and 2: was it a few generations or millions of years? In scenario 1, molecules X and Y must be identical, whereas in scenario 2 they could have any level of sequence divergence from minimal to extensive, and they could also differ by chromosomal rearrangements. It has been difficult to design tests that could differentiate between these scenarios, but an analysis of the inferred order of genes along molecules X and Y did not find any rearrangements and so did not rule out scenario 1 [9]. However, it has been frustrating that we could not pin down the details of this crucial phase of yeast evolution, which gave birth to many pairs of genes with substantially divergent functions [11–15].In this issue of PLOS Biology, Marcet-Houben and Gabaldón now report strong evidence in support of interspecies hybridization (scenario 2) as the source of the two subgenomes in post-WGD species [16]. By phylogenetic analysis using state-of-the-art methods, they show that molecules X and Y have phylogenetic affinities to two different non-WGD lineages that they call the KLE and ZT clades. The KLE clade (Kluyveromyces, Lachancea, and Eremothecium) is the group of non-WGD species that was sequenced in 2004 [5–7]. The ZT clade (Zygosaccharomyces and Torulaspora) is a separate, more recently studied non-WGD lineage [17,18]. Previous phylogenetic studies using supertrees or concatenated data suggested that the ZT clade is sister to the post-WGD clade, with the KLE clade being an out-group to them both [17,19,20]. The new analysis [16] made trees for each gene individually and found that, although the majority of genes in post-WGD species do cluster phylogenetically with the ZT clade as expected, a significant minority (about 30%) instead either cluster with the KLE clade or form an outgroup to a KLE + ZT clade. This phylogenetic heterogeneity was not noticed before because the KLE signal is only present in a minority of genes, and it is swamped by the ZT signal in methods that try to place the post-WGD clade at a single point on the tree.Marcet-Houben and Gabaldón interpret this phylogenetic heterogeneity as evidence that the two post-WGD subgenomes have separate origins, one from the ZT clade and the other from an unidentified lineage that is an outgroup to KLE + ZT. Under the simplest hypothesis of hybridization, we might then expect that phylogenetic trees constructed from ohnolog pairs should show one S. cerevisiae gene grouping with the ZT clade and the other grouping with the KLE clade, but in fact, most ohnolog pairs group with each other, with the ZT clade as their closest relative [16]. The authors’ explanation for these two results—an excess of ZT-like ohnolog pairs, and an excess of ZT-like genes in the whole genome (which is mostly singletons)—is that the post-WGD genomes have been affected by biased gene conversion that preferentially replaced some KLE-derived sequences with copies of the homeologous ZT-derived sequences, homogenizing these regions and obliterating their signal of KLE ancestry.The hybridization proposed by Marcet-Houben and Gabaldón makes a lot of sense in terms of what we know about the biology of yeast interspecies hybrids. Many yeast strains, most notably those used in commercial settings where stress tolerance is important, have turned out to be interspecies hybrids. For instance, the yeast used to brew lager (S. pastorianus) is a hybrid between S. cerevisiae and S. eubayanus [21,22], and many other combinations of genomes from different species of Saccharomyces have been found in nature [23]. These interspecies hybrids are usually infertile (unable to sporulate) because the two copies (homeologs) of each chromosome that they contain are too dissimilar to pair properly during meiosis [24–26]. One simple way to restore fertility is to double the genome, allowing each chromosome to pair with an identical partner instead of trying to pair with the homeolog. In this model, cell Z changes from being a nonmater (effectively diploid) to a mater (effectively haploid—perhaps by deletion of a MAT allele), then two cells of type Z mate to produce cell ZZ (diploid), and cell ZZ is able to go through meiosis and make spores with twice the DNA content of cell W. Thus, one hypothesis that Marcet-Houben and Gabaldón propose is that event 2 was an interspecies mating and event 3 was a restoration of fertility by genome doubling, with a possible interval of many mitotic generations between these two events. Alternatively, they hypothesize that event 2 may have been an interspecies fusion of diploid cells, obviating the need for a separate event 3.The obscuring of the phylogenetic signal of hybridization by subsequent gene conversions [16] is consistent with the known genome structures of some interspecies hybrids. The yeasts Pichia sorbitophila [27] and Candida orthopsilosis [28] are both interspecies hybrids, but in each case extensive homogenization of parts of the genome has occurred. This process of homogenization has been called overwriting, loss of heterozygosity, or gene conversion by different groups. It leaves the number of chromosomes unchanged (equal to the sum of the numbers of chromosomes in the two incoming subgenomes) but involves the replacement of sequences in one subgenome by sequences copied from the other subgenome (cell H in Fig 2). Homogenization could occur on scales as small as a few hundred base pairs (gene conversion) or as large as whole chromosome arms (break-induced replication). In the latter case, even differences in gene order such as inversions between the parental species could be ironed out.The discovery that the yeast WGD was an allopolyploidization adds complexity to what initially seemed to be a simple story of duplication. If an interspecies hybrid such as P. sorbitophila with a partly homogenized genome developed two mating types and these could mate to form a diploid that could sporulate efficiently, the result would be a species with a genome resembling the inferred progenitor of the post-WGD clade (cell HH in Fig 2). Allopolyploidy answers some old questions about why genes were retained in duplicate if their sequences were identical (answer: they weren’t identical), what the immediate selective advantage of the post-WGD cell was (answer: hybrid vigor), and how the post-WGD lineage became reproductively isolated from the pre-WGD lineage (answer: delay between events 2 and 3). But it also raises new questions about homogenization (how much of the genome? how often? why is it biased?) and about the mechanism of restoration of fertility (why is event 3 so rare, apparently happening only once in the budding yeast family even though event 2 happened quite often?).Ancient WGDs have been detected right across the eukaryotic tree of life, including in animals, ciliates, fungi, and, most prominently, plants [29–32]. If extensive gene conversion can obscure the traces of allopolyploidization in yeast genomes, one might wonder how many of these other ancient WGDs also began as interspecies hybridizations. In fact, there is evidence from plants that gene conversion acts continually to homogenize ohnolog pairs [32,33] and that hybrid plants can show preferential retention of DNA from one parent over the other [34] similar to the situation in P. sorbitophila [27]. Detecting the yeast hybridization in the presence of these obscuring factors required both good luck and good timing: good luck that a reference species closer to one parent than to the other had been sequenced and good timing that the hybrid was sampled before all traces of its hybrid origin had faded away. These fortunate circumstances may not hold for ancient hybridizations in other eukaryotes, but as a famous golfer once said, “The harder I practice, the luckier I get.” Detecting that they are hybridizations may become possible with exhaustive sampling of possible parental lineages and the use of sensitive phylogenomic methods of the type introduced by the authors [16].     

Caring for Offspring in a World of Cheats

Parents providing care to offspring face the same problem that exists in every biological system in which some individuals offer resources to others: cheaters, who exploit these benefits. In almost all species in which males contribute to parental care, females mate with multiple males. As a result, males frequently provide efforts for unrelated offspring at a cost to their own reproductive fitness. In a new study, Griffin et al. find that across a wide range of animal species, males flexibly adjust their contribution to parental care in relation to extra-pair paternity. However, adjustment is not perfect, because males are limited by the potential costs of withholding help to their own offspring, which is only outweighed if cheating occurs frequently and if providing care reduces a male''s future reproductive success. These findings illustrate how in biological systems cheater and cheated can adapt to changes in each other, preventing either one from gaining control.Whatever your personal feelings, evolutionary biologists will tell you that caring for offspring is not an easy affair. Pick up any current textbook on behavioural ecology, and you will find that the word “family” is invariably followed by the word “conflict” (e.g., [1]). Conflicts between family members arise because selection favours individuals aiming to maximize reproductive fitness, and these aims frequently collide because selection pressures differ even among related individuals [2]–[4]. Offspring can improve their reproductive fitness by obtaining the maximal amount of investment from both of their parents. However, parents frequently provide less than the maximum because any increased investment into current offspring impacts their ability to produce additional offspring in the future. Caring for offspring in all its forms is energetically expensive and may impair a parent''s ability to have additional offspring in a variety of ways. For example, when a female of the golden egg bug (Phyllomorpha laciniata) lays her eggs on a male rather than on a plant, her offspring will have increased survival, but the father carrying the eggs has a higher risk of being eaten by a bird [5]. In bighorn sheep (Ovis canadiensis) [6], mothers are less likely to have a surviving offspring in the year after rearing a son, as males are generally heavier at birth and suckle more frequently because being larger provides an advantage when competing against other males. In European starlings (Sturnus vulgaris), males who participate less in the incubation of the offspring have a higher chance of gaining a secondary female [7].Given the costs of providing parental care, we would expect that individuals should not expend energy if they do not gain any fitness at all, as is the case when they care for offspring that are not their own [2],[8]–[10]. Individuals that are potential victims of cheating are predicted to have evolved a range of counteradaptations to reduce the risks and costs of raising unrelated offspring [11],[12] ([13].

Table 1

Strategies to minimize the risks and costs of being exploited by cheaters.

Harnessing Evolution to Elucidate the Consequences of Symbiosis

Many organisms harbor microbial associates that have profound impacts on host traits. The phenotypic effect of symbionts on their hosts may include changes in development, reproduction, longevity, and defense against natural enemies. Determining the consequences of associating with a microbial symbiont requires experimental comparison of hosts with and without symbionts. Then, determining the mechanism by which symbionts alter these phenotypes can involve genomic, genetic, and evolutionary approaches; however, many host-associated symbionts are not amenable to genetic approaches that require cultivation of the microbe outside the host. In the current issue of PLOS Biology, Chrostek and Teixeira highlight an elegant approach to studying functional mechanisms of symbiont-conferred traits. They used directed experimental evolution to select for strains of Wolbachia wMelPop (a bacterial symbiont of fruit flies) that differed in copy number of a region of the genome suspected to underlie virulence. Copy number evolved rapidly when under selection, and wMelPop strains with more copies of the region shortened the lives of their Drosophila hosts more than symbionts with fewer copies. Interestingly, the wMelPop strains with more copies also increase host resistance to viruses compared to symbionts with fewer copies. Their study highlights the power of exploiting alternative approaches when elucidating the functional impacts of symbiotic associations.Symbioses, long-term and physically close interactions between two or more species, are central to the ecology and evolution of many organisms. Though “Symbiosis” is more often used to define interactions that are presumed to be mutually beneficial to a host and its microbial partner, a broader definition including both parasitic and mutualistic interactions recognizes that the fitness effects of many symbioses are complex and often context dependent. Whether an association is beneficial can depend on ecological conditions, and mutation and other evolutionary processes can result in symbiont strains that differ in terms of costs and benefits to hosts (Fig. 1).Open in a separate windowFig 1The symbiosis spectrum.The costs and benefits of symbiosis for hosts are not bimodal but span a continuum. The benefit to cost ratio is mediated both by environmental conditions and by the strain of symbiont. For example, the bacteria Hamiltonella defensa increases aphid resistance to parasitoid wasps. When Hamiltonella loses an associated bacteriophage, protection is lost. Also, in aphids, Buchnera aphidicola is a bacterial symbiont that provisions its hosts with critical nutritional resources. However, alterations of the heat shock promoter in Buchnera lessen the fitness benefit of symbiosis for the hosts under elevated temperatures. Amplification of a region of the Wolbachia genome known as Octomom causes the bacteria to shorten the lifespan of its Drosophila fly hosts.Elucidating the effects of host-associated microbes includes, when possible, experiments designed to assay host phenotypes when they do and do not have a particular symbiont of interest (Fig. 2). In systems in which hosts acquire symbionts from the environment, hosts can be reared in sterile conditions to prevent acquisition [1]. If symbionts are passed internally from mother to offspring, antibiotic treatments can sometimes be utilized to obtain lineages of hosts without symbionts [2]. The impacts of symbiont presence on survival, development, reproduction, and defense can be quantified, with the caveat that these impacts may be quite different under alternative environmental conditions. While such experiments are sometimes more tractable in systems with simple microbial consortia, the same experimental processes can be utilized in systems with more complex microbial communities [3,4].Open in a separate windowFig 2Approaches to functionally characterize symbiont effects.The first step in functionally characterizing the phenotypic impacts of a symbiont on its host is to measure phenotypes of hosts with and without symbionts. Any effects need to be considered in the light of how they are modified by environmental conditions. Understanding the mechanisms underlying symbiont alteration of host phenotype can involve, and often combines, genomic, genetic, and evolutionary approaches. Solid arrows indicate the path leading to results highlighted in Chrostek and Teixeira’s investigation of Wolbachia virulence in this issue of PLoS Biology.Once a fitness effect of symbiosis is ascertained, determining the mechanistic basis of this effect can be challenging. A genomics approach sometimes provides informative insight into microbial function. Sequencing of many insect-associated symbionts, for example, has confirmed the presence of genes necessary for amino acid and vitamin synthesis [5–8]. These genomic revelations, in some cases, can be linked to phenotypic effects of symbiosis for the hosts. For example, aphids reared in the absence of their obligate symbiotic bacteria, Buchnera aphidicola, can survive when provisioned with supplemental amino acids but cannot survive without supplementation, suggesting that Buchnera’s provisioning of amino acids is critical for host survival [9,10]. The Buchnera genome contains many of the genes necessary for amino acid synthesis [5].Linking genotype to phenotype, however, can be complicated. Experiments are necessary to functionally test the insights garnered from genome sequencing. For example, just because a symbiont has genes necessary for synthesis of a particular nutrient does not mean that the nutrient is being provisioned to its host. Furthermore, in many systems we do not know what genetic mechanisms are most likely to influence a symbiont-conferred phenotype. For example, if hosts associated with a given microbe have lower fitness than those without the microbe, what mechanism mediates this phenotype? Is it producing a toxin? Is it using too many host resources? In these cases, a single genome provides even less insight.Comparative genomics can be another approach. This requires collection of hosts with alternative symbiont strains and then testing these strains in a common host background to demonstrate that they have different phenotypic effects. Symbiont genomes can then be sequenced and compared to identify differences. This approach was utilized to compare genomes of strains of the aphid bacterial symbiont Regiella insecticola that confer different levels of resistance to parasitoid wasps [11]; the protective and nonprotective Regiella genome differed in many respects. Comparing the genomes of Wolbachia strains with differential impacts on fly host fitness [12,13] revealed fewer differences, though none involved a gene with a function known to impact host fitness. Comparative genomics rarely uncovers a holy grail as the genomes of symbiont strains with alternative phenotypic effects rarely differ at a single locus of known function.Another approach, which is at the heart of studies of microbial pathogens, is to use genetic tools to manipulate symbionts at candidate loci (or randomly through mutagenesis) and compare the phenotypic effects of genetically-manipulated and unmanipulated symbionts. Indeed, this approach has provided insights into genes underlying traits of both pathogenic [14] and beneficial [15,16] microbes. There is one challenge. Many host-associated symbionts are not cultivable outside of their hosts, which precludes utilization of most traditional genetic techniques used to modify microbial genomes.An alternative approach to studying symbiont function leverages evolution. Occasionally, lineages that once conferred some phenotypic effect, when tested later, no longer do. If symbiont samples were saved along the way, researchers can then determine what in the genome changed. For example, pea aphids (Acyrthosiphon pisum) harboring the bacteria Hamiltonella defensa are more resistant to parasitoid wasps than those without the bacteria [17,18]. Toxin-encoding genes identified in the genome of a Hamiltonella-associated bacteriophage were hypothesized to be central to this defense [18,19]. However, confirmation of the bacteriophage’s role required comparing the insects’ resistance to wasps when they harbored the same Hamiltonella with and without the phage. No Hamiltonella isolates were found in nature without the phage, but bottleneck passaging of the insects and symbionts generation after generation in the laboratory led to the loss of phage in multiple host lineages. Experimental assays confirmed that in the absence of phage, there was no protection [20]. Similarly, laboratory passaging of aphids and symbionts serendipitously led to spread of a mutation in the genome of Buchnera aphidicola, the primary, amino acid-synthesizing symbiont of pea aphids. The mutation, a single nucleotide deletion in the promoter for ibpA, a gene encoding for a heat-shock protein, lowers aphid fitness under elevated temperature conditions [21]. The mutation is found at low levels in natural aphid populations, suggesting that laboratory conditions facilitate maintenance of the genotype.In the above cases, evolution was a fortunate coincidence. In this issue of PLoS Biology, Chrostek and Teixeira (2014) illustrate another alternative, directed experimental evolution. Previous work demonstrated that a strain of the symbiotic bacterium Wolbachia, wMelPop, is virulent to its Drosophila melanogaster hosts, considerably shortening lifespan while overproliferating inside the flies [22]. To investigate the mechanism of virulence, researchers compared the genomic content of an avirulent Wolbachia strain to that of the virulent wMelPop [12,13]. These comparisons revealed that the wMelPop genome contains a region with eight genes that is amplified multiple times; in avirulent strains there is only a single copy. This eight gene region was nicknamed “Octomom.” To functionally test whether Octomom mediates Wolbachia virulence, over successive generations, Chrostek and Teixeira selected for females with either high or low Octomom copy numbers to start the next generations. They found that copy number could evolve rapidly and was correlated with virulence. Flies harboring wMelPop with more copies of Octomom had shorter lifespans. This cost was reversed in the presence of natural enemies; flies harboring wMelPop with more copies of Octomom had higher resistance to viral pathogens. Thus, selection provided a functional link between genotype and phenotype in a symbiont recalcitrant to traditional microbial genetics approaches.In many respects, this is similar to the research on aphids and their symbionts, where protective phenotypes were lost through passaging of aphids and symbionts generation after generation, as part of standard laboratory maintenance. Chrostek and Teixeira simply used the tools of experimental evolution to select for altered symbionts in a controlled fashion. Comparison of the studies also highlights two potential approaches—select for a phenotype and determine the genotypic change, or select for a genotype of interest and determine the phenotypic effect.Why do we need to know the genetic mechanisms underlying symbiont-conferred traits? In terms of evolutionary dynamics, the maintenance of a symbiont’s effect in a population is predicated on the likelihood of it being maintained in the presence of mutation, drift, and selection. Symbiosis research often considers how ecological conditions influence symbiont-conferred traits but less often considers the instability of those influences due to evolutionary change. From the perspective of applied applications to human concerns, symbiont alteration of insect phenotypes are potential mechanisms to reduce vectoring of human and agricultural pathogens, either through directly reducing insect fitness or reducing the capacity of vectors to serve as pathogen reservoirs [23–28]. Short term field trials, for example, have demonstrated spread and persistence of Wolbachia in mosquito populations [29,30]. Because Wolbachia reduce persistence of viruses, including human pathogens, in insects [26,31–33], this is a promising pesticide-free and drug-free control strategy for insect-vectored diseases. Can we assume that Wolbachia and other symbionts will always confer the same phenotypes to their hosts? If the conferred phenotype is based on a region of the genome where mutation is likely (e.g., the homopolymeric track within the heat shock promoter of aphid Buchnera, the Octomom region in Drosophila wMelPop), then we have clear reason to suspect that the genotypic and phenotypic makeup of the symbiont population could change over time. We need to investigate how populations of bacterial symbionts evolve in host populations under natural ecological conditions, carefully screening for both changes in phenotype and changes in genotype over the course of such experimental observations. We then need to incorporate evolutionary changes when modeling symbiont maintenance and when considering the use of symbionts in applied applications.     

Centre of the Cell: Science Comes to Life

Centre of the Cell is a unique biomedical science education centre, a widening participation and outreach project in London’s East End. This article describes Centre of the Cell’s first five years of operation, the evolution of the project in response to audience demand, and the impact of siting a major public engagement project within a research laboratory.Centre of the Cell is a unique cell-shaped science centre suspended above a real biomedical research laboratory in the heart of London’s East End. It is one of the few, perhaps the only, science education centres in the world to be situated inside a research lab—in the Blizard Institute at the Whitechapel medical and dental campus of Queen Mary University of London (QMUL). Since its opening in September 2009, over 100,000 people have participated in Centre of the Cell activities (Fig 1) with approximately one million visits to the interactive website www.centreofthecell.org. With visitor numbers and activities increasing year on year, we believe this is an example of an innovative and successful public engagement project that may serve as an example for similar initiatives in biomedical research institutes.Open in a separate windowFig 1Visitor statistics for Centre of the Cell years 3–6 (2011–2015).These monthly statistics include all visitors on site as well as visitors to our workshops and shows in schools and other locations. Year 1 and 2 figures (not shown here) were 15,387 and 19,585, respectively. These data show a consistent pattern from month to month. 2013–2014 numbers were lower, due to planned maintenance shutdown of the Pod and introduction of charging for Pod shows that led to a dip in visitor numbers that largely recovered during 2014.     

Cyclophilin D in mitochondrial pathophysiology

Cyclophilins are a family of peptidyl-prolyl cis–trans isomerases whose enzymatic activity can be inhibited by cyclosporin A. Sixteen cyclophilins have been identified in humans, and cyclophilin D is a unique isoform that is imported into the mitochondrial matrix. Here we shall (i) review the best characterized functions of cyclophilin D in mitochondria, i.e. regulation of the permeability transition pore, an inner membrane channel that plays an important role in the execution of cell death; (ii) highlight new regulatory interactions that are emerging in the literature, including the modulation of the mitochondrial F1FO ATP synthase through an interaction with the lateral stalk of the enzyme complex; and (iii) discuss diseases where cyclophilin D plays a pathogenetic role that makes it a suitable target for pharmacologic intervention.     

High-affinity inhibitors of human NAD-dependent 15-hydroxyprostaglandin dehydrogenase: mechanisms of inhibition and structure-activity relationships

Background

15-hydroxyprostaglandin dehydrogenase (15-PGDH, EC 1.1.1.141) is the key enzyme for the inactivation of prostaglandins, regulating processes such as inflammation or proliferation. The anabolic pathways of prostaglandins, especially with respect to regulation of the cyclooxygenase (COX) enzymes have been studied in detail; however, little is known about downstream events including functional interaction of prostaglandin-processing and -metabolizing enzymes. High-affinity probes for 15-PGDH will, therefore, represent important tools for further studies.

Principal Findings

To identify novel high-affinity inhibitors of 15-PGDH we performed a quantitative high-throughput screen (qHTS) by testing >160 thousand compounds in a concentration-response format and identified compounds that act as noncompetitive inhibitors as well as a competitive inhibitor, with nanomolar affinity. Both types of inhibitors caused strong thermal stabilization of the enzyme, with cofactor dependencies correlating with their mechanism of action. We solved the structure of human 15-PGDH and explored the binding modes of the inhibitors to the enzyme in silico. We found binding modes that are consistent with the observed mechanisms of action.

Conclusions

Low cross-reactivity in screens of over 320 targets, including three other human dehydrogenases/reductases, suggest selectivity of the present inhibitors for 15-PGDH. The high potencies and different mechanisms of action of these chemotypes make them a useful set of complementary chemical probes for functional studies of prostaglandin-signaling pathways.

Enhanced version

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