From the Cover: Unbiased screen for interactors of leucine-rich repeat kinase 2 supports a common pathway for sporadic and familial Parkinson disease

Mutations in leucine-rich repeat kinase 2 (LRRK2) cause inherited Parkinson disease (PD), and common variants around LRRK2 are a risk factor for sporadic PD. Using protein–protein interaction arrays, we identified BCL2-associated athanogene 5, Rab7L1 (RAB7, member RAS oncogene family-like 1), and Cyclin-G–associated kinase as binding partners of LRRK2. The latter two genes are candidate genes for risk for sporadic PD identified by genome-wide association studies. These proteins form a complex that promotes clearance of Golgi-derived vesicles through the autophagy–lysosome system both in vitro and in vivo. We propose that three different genes for PD have a common biological function. More generally, data integration from multiple unbiased screens can provide insight into human disease mechanisms.Genetics contribute to the pathogenesis of Parkinson disease (PD) in two ways. Mutations in several genes can cause inherited PD (1), and risk factor variants contribute to the risk of sporadic PD (2). Some genes contribute to both mechanisms. These pleomorphic risk loci (3) include genes that encode α-synuclein and leucine-rich repeat kinase 2 (LRRK2) (4). However, risk factors for sporadic PD identified by genome-wide association studies (GWASs) (5–9) actually nominate large genomic loci with multiple candidate genes (10). These loci may include variants that change amino acids or affect disease risk through gene expression (11). Also, whether all of the genes for PD converge on a small number of biological pathways is unknown (1). It is, therefore, important to develop unbiased approaches that would resolve whether genes for PD have similar biological functions and understand the mechanism(s) of disease risk. Here, we examine one genetic cause of PD (LRRK2) and show that identifying protein interaction partners can clarify disease mechanisms.     

Convergent evolution toward an improved growth rate and a reduced resistance range in Prochlorococcus strains resistant to phage

Prochlorococcus is an abundant marine cyanobacterium that grows rapidly in the environment and contributes significantly to global primary production. This cyanobacterium coexists with many cyanophages in the oceans, likely aided by resistance to numerous co-occurring phages. Spontaneous resistance occurs frequently in Prochlorococcus and is often accompanied by a pleiotropic fitness cost manifested as either a reduced growth rate or enhanced infection by other phages. Here, we assessed the fate of a number of phage-resistant Prochlorococcus strains, focusing on those with a high fitness cost. We found that phage-resistant strains continued evolving toward an improved growth rate and a narrower resistance range, resulting in lineages with phenotypes intermediate between those of ancestral susceptible wild-type and initial resistant substrains. Changes in growth rate and resistance range often occurred in independent events, leading to a decoupling of the selection pressures acting on these phenotypes. These changes were largely the result of additional, compensatory mutations in noncore genes located in genomic islands, although genetic reversions were also observed. Additionally, a mutator strain was identified. The similarity of the evolutionary pathway followed by multiple independent resistant cultures and clones suggests they undergo a predictable evolutionary pathway. This process serves to increase both genetic diversity and infection permutations in Prochlorococcus populations, further augmenting the complexity of the interaction network between Prochlorococcus and its phages in nature. Last, our findings provide an explanation for the apparent paradox of a multitude of resistant Prochlorococcus cells in nature that are growing close to their maximal intrinsic growth rates.Large bacterial populations are present in the oceans, playing important roles in primary production and the biogeochemical cycling of matter. These bacterial communities are highly diverse (1–4) yet form stable and reproducible bacterial assemblages under similar environmental conditions (5–7).These bacteria are present together with high abundances of viruses (phages) that have the potential to infect and kill them (8–11). Although studied only rarely in marine organisms (12–16), this coexistence is likely to be the result of millions of years of coevolution between these antagonistic interacting partners, as has been well documented for other systems (17–20). From the perspective of the bacteria, survival entails the selection of cells that are resistant to infection, preventing viral production and enabling the continuation of the cell lineage. Resistance mechanisms include passively acquired spontaneous mutations in cell surface molecules that prevent phage entry into the cell and other mechanisms that actively terminate phage infection intracellularly, such as restriction–modification systems and acquired resistance by CRISPR-Cas systems (21, 22). Mutations in the phage can also occur that circumvent these host defenses and enable the phage to infect the recently emerged resistant bacterium (23).Acquisition of resistance by bacteria is often associated with a fitness cost. This cost is frequently, but not always, manifested as a reduction in growth rate (24–27). Recently, an additional type of cost of resistance was identified, that of enhanced infection whereby resistance to one phage leads to greater susceptibility to other phages (14, 15, 28).Over the years, a number of models have been developed to explain coexistence in terms of the above coevolutionary processes and their costs (16, 29–32). In the arms race model, repeated cycles of host mutation and virus countermutation occur, leading to increasing breadths of host resistance and viral infectivity. However, experimental evidence generally indicates that such directional arms race dynamics do not continue indefinitely (25, 33, 34). Therefore, models of negative density-dependent fluctuations due to selective trade-offs, such as kill-the-winner, are often invoked (20, 33, 35, 36). In these models, fluctuations are generally considered to occur between rapidly growing competition specialists that are susceptible to infection and more slowly growing resistant strains that are considered defense specialists. Such negative density-dependent fluctuations are also likely to occur between strains that have differences in viral susceptibility ranges, such as those that would result from enhanced infection (30).The above coevolutionary processes are considered to be among the major mechanisms that have led to and maintain diversity within bacterial communities (32, 35, 37–39). These processes also influence genetic microdiversity within populations of closely related bacteria. This is especially the case for cell surface-related genes that are often localized to genomic islands (14, 40, 41), regions of high gene content, and gene sequence variability among members of a population. As such, populations in nature display an enormous degree of microdiversity in phage susceptibility regions, potentially leading to an assortment of subpopulations with different ranges of susceptibility to coexisting phages (4, 14, 30, 40).Prochlorococcus is a unicellular cyanobacterium that is the numerically dominant photosynthetic organism in vast oligotrophic expanses of the open oceans, where it contributes significantly to primary production (42, 43). Prochlorococcus consists of a number of distinct ecotypes (44–46) that form stable and reproducible population structures (7). These populations coexist in the oceans with tailed double-stranded DNA phage populations that infect them (47–49).Previously, we found that resistance to phage infection occurs frequently in two high-light–adapted Prochlorococcus ecotypes through spontaneous mutations in cell surface-related genes (14). These genes are primarily localized to genomic island 4 (ISL4) that displays a high degree of genetic diversity in environmental populations (14, 40). Although about a third of Prochlorococcus-resistant strains had no detectable associated cost, the others came with a cost manifested as either a slower growth rate or enhanced infection by other phages (14). In nature, Prochlorococcus seems to be growing close to its intrinsic maximal growth rate (50–52). This raises the question as to the fate of emergent resistant Prochlorococcus lineages in the environment, especially when resistance is accompanied with a high growth rate fitness cost.To begin addressing this question, we investigated the phenotype of Prochlorococcus strains with time after the acquisition of resistance. We found that resistant strains evolved toward an improved growth rate and a reduced resistance range. Whole-genome sequencing and PCR screening of many of these strains revealed that these phenotypic changes were largely due to additional, compensatory mutations, leading to increased genetic diversity. These findings suggest that the oceans are populated with rapidly growing Prochlorococcus cells with varying degrees of resistance and provide an explanation for how a multitude of presumably resistant Prochlorococcus cells are growing close to their maximal known growth rate in nature.     

Distinct dopamine neurons mediate reward signals for short- and long-term memories

Drosophila melanogaster can acquire a stable appetitive olfactory memory when the presentation of a sugar reward and an odor are paired. However, the neuronal mechanisms by which a single training induces long-term memory are poorly understood. Here we show that two distinct subsets of dopamine neurons in the fly brain signal reward for short-term (STM) and long-term memories (LTM). One subset induces memory that decays within several hours, whereas the other induces memory that gradually develops after training. They convey reward signals to spatially segregated synaptic domains of the mushroom body (MB), a potential site for convergence. Furthermore, we identified a single type of dopamine neuron that conveys the reward signal to restricted subdomains of the mushroom body lobes and induces long-term memory. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct dopamine neurons.Memory of a momentous event persists for a long time. Whereas some forms of long-term memory (LTM) require repetitive training (1–3), a highly relevant stimulus such as food or poison is sufficient to induce LTM in a single training session (4–7). Recent studies have revealed aspects of the molecular and cellular mechanisms of LTM formation induced by repetitive training (8–11), but how a single training induces a stable LTM is poorly understood (12).Appetitive olfactory learning in fruit flies is suited to address the question, as a presentation of a sugar reward paired with odor induces robust short-term memory (STM) and LTM (6, 7). Odor is represented by a sparse ensemble of the 2,000 intrinsic neurons, the Kenyon cells (13). A current working model suggests that concomitant reward signals from sugar ingestion cause associative plasticity in Kenyon cells that might underlie memory formation (14–20). A single activation session of a specific cluster of dopamine neurons (PAM neurons) by sugar ingestion can induce appetitive memory that is stable over 24 h (19), underscoring the importance of sugar reward to the fly.The mushroom body (MB) is composed of the three different cell types, α/β, α′/β′, and γ, which have distinct roles in different phases of appetitive memories (11, 21–25). Similar to midbrain dopamine neurons in mammals (26, 27), the structure and function of PAM cluster neurons are heterogeneous, and distinct dopamine neurons intersect unique segments of the MB lobes (19, 28–34). Further circuit dissection is thus crucial to identify candidate synapses that undergo associative modulation.By activating distinct subsets of PAM neurons for reward signaling, we found that short- and long-term memories are independently formed by two complementary subsets of PAM cluster dopamine neurons. Conditioning flies with nutritious and nonnutritious sugars revealed that the two subsets could represent different reinforcing properties: sweet taste and nutritional value of sugar. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct reward signals.     

Recombinant transfer in the basic genome of Escherichia coli

An approximation to the ∼4-Mbp basic genome shared by 32 strains of Escherichia coli representing six evolutionary groups has been derived and analyzed computationally. A multiple alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ∼90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single base-pair mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly between genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome pairs have one or two recombinant transfers of length ∼40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kilobase pairs. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. Most recombinant transfers seem likely to be due to generalized transduction by coevolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.The increasing availability of complete genome sequences of many different bacterial and archaeal species, as well as metagenomic sequencing of mixed populations from natural environments, has stimulated theoretical and computational approaches to understand mechanisms of speciation and how prokaryotic species should be defined (1–8). Much genome analysis and comparison has been at the level of gene content, identifying core genomes (the set of genes found in most or all genomes in a group) and the continually expanding pan-genome. Population genomics of Escherichia coli has been particularly well studied because of its long history in laboratory research and because many pathogenic strains have been isolated and completely sequenced (9–14). Proposed models of how related groups or species form and evolve include isolation by ecological niche (7–9, 11, 15), decreased homologous recombination as divergence between isolated populations increases (2–4, 8, 14, 16), and coevolving phage and bacterial populations (6).E. coli genomes are highly variable, containing an array of phage-related mobile elements integrated at many different sites (17), random insertions of multiple transposable elements (18), and idiosyncratic genome rearrangements that include inversions, translocations, duplications, and deletions. Although E. coli grows by binary cell division, genetic exchange by homologous recombination has come to be recognized as a significant factor in adaptation and genome evolution (9, 10, 19). Of particular interest has been the relative contribution to genome variability of random mutations (single base-pair differences referred to as SNPs) and replacement of genome regions by homologous recombination with fragments imported from other genomes (here referred to as recombinant transfers or transferred regions). Estimates of the rate, extent, and average lengths of recombinant transfers in the core genome vary widely, as do methods for detecting transferred regions and assessing their impact on phylogenetic relationships (12–14, 20, 21).In a previous comparison of complete genome sequences of the K-12 reference strain MG1655 and the reconstructed genome of the B strain of Delbrück and Luria referred to here as B-DL, we observed that SNPs are not randomly distributed among 3,620 perfectly matched pairs of coding sequences but rather have two distinct regimes: sharply decreasing numbers of genes having 0, 1, 2, or 3 SNPs, and an abrupt transition to a much broader exponential distribution in which decreasing numbers of genes contain increasing numbers of SNPs from 4 to 102 SNPs per gene (22). Genes in the two regimes of the distribution are interspersed in clusters of variable lengths throughout what we referred to as the basic genome, namely, the ∼4 Mbp shared by the two genomes after eliminating mobile elements. We speculated that genes having 0 to 3 SNPs may primarily have been inherited clonally from the last common ancestor, whereas genes comprising the exponential tail may primarily have been acquired by horizontal transfer from diverged members of the population.The current study was undertaken to extend these observations to a diverse set of 32 completely sequenced E. coli genomes and to analyze how SNP distributions in the basic genome change as a function of evolutionary divergence between the 496 pairs of strains in this set. We have taken a simpler approach than those of Touchon et al. (13), Didelot et al. (14), and McNally et al. (21), who previously analyzed multiple alignments of complete genomes of E. coli strains. The appreciably larger basic genome derived here is not restricted to protein-coding sequences and retains positional information.     

Toxin Kid uncouples DNA replication and cell division to enforce retention of plasmid R1 in Escherichia coli cells

Worldwide dissemination of antibiotic resistance in bacteria is facilitated by plasmids that encode postsegregational killing (PSK) systems. These produce a stable toxin (T) and a labile antitoxin (A) conditioning cell survival to plasmid maintenance, because only this ensures neutralization of toxicity. Shortage of antibiotic alternatives and the link of TA pairs to PSK have stimulated the opinion that premature toxin activation could be used to kill these recalcitrant organisms in the clinic. However, validation of TA pairs as therapeutic targets requires unambiguous understanding of their mode of action, consequences for cell viability, and function in plasmids. Conflicting with widespread notions concerning these issues, we had proposed that the TA pair kis-kid (killing suppressor-killing determinant) might function as a plasmid rescue system and not as a PSK system, but this remained to be validated. Here, we aimed to clarify unsettled mechanistic aspects of Kid activation, and of the effects of this for kis-kid–bearing plasmids and their host cells. We confirm that activation of Kid occurs in cells that are about to lose the toxin-encoding plasmid, and we show that this provokes highly selective restriction of protein outputs that inhibits cell division temporarily, avoiding plasmid loss, and stimulates DNA replication, promoting plasmid rescue. Kis and Kid are conserved in plasmids encoding multiple antibiotic resistance genes, including extended spectrum β-lactamases, for which therapeutic options are scarce, and our findings advise against the activation of this TA pair to fight pathogens carrying these extrachromosomal DNAs.Plasmids serve as extrachromosomal DNA platforms for the reassortment, mobilization, and maintenance of antibiotic resistance genes in bacteria, enabling host cells to colonize environments flooded with antimicrobials and to take advantage of resources freed by the extinction of nonresistant competitors. Fueled by these selective forces and aided by their itinerant nature, plasmids disseminate resistance genes worldwide shortly after new antibiotics are developed, which is a major clinical concern (1–3). However, in antibiotic-free environments, such genes are dispensable. There, the cost that plasmid carriage imposes on cells constitutes a disadvantage in the face of competition from other cells and, because plasmids depend on their hosts to survive, also a threat to their own existence.Many plasmids keep low copy numbers (CNs) to minimize the problem above, because it reduces burdens to host cells. However, this also decreases their chances to fix in descendant cells, a new survival challenge (4). To counteract this, plasmids have evolved stability functions. Partition systems pull replicated plasmid copies to opposite poles in host cells, facilitating their inheritance by daughter cells (5). Plasmids also bear postsegregational killing (PSK) systems, which encode a stable toxin and a labile antitoxin (TA) pair that eliminates plasmid-free cells produced by occasional replication or partition failures. Regular production of the labile antitoxin protects plasmid-containing cells from the toxin. However, antitoxin replenishment is not possible in cells losing the plasmid, and this triggers their elimination (5).TA pairs are common in plasmids disseminating antibiotic resistance in bacterial pathogens worldwide (2, 6–10). The link of these systems to PSK and the exiguous list of alternatives in the pipeline have led some to propose that chemicals activating these TA pairs may constitute a powerful antibiotic approach against these organisms (5, 11–13). However, the appropriateness of these TA pairs as therapeutic targets requires unequivocal understanding of their function in plasmids. Although PSK systems encode TA pairs, not all TA pairs might function as PSK systems, as suggested by their abundance in bacterial chromosomes, where PSK seems unnecessary (14–16). Moreover, the observation that many plasmids bear several TA pairs (6–10) raises the intriguing question of why they would need more than one PSK system, particularly when they increase the metabolic burden that plasmids impose on host cells (17). Because PSK functions are not infallible, their gathering may provide a mechanism for reciprocal failure compensation, minimizing the number of cells that escape killing upon plasmid loss (5). Alternatively, some TA pairs may stabilize plasmids by mechanisms different from PSK, and their grouping might not necessarily reflect functional redundancy (18).This may be the case in plasmid R1, which encodes TA pairs hok-sok (host killing-suppressor of killing) and kis(pemI)-kid(pemK) (19–23). Inconsistent with PSK, we had noticed that activation of toxin Kid occurred in cells that still contained R1, and that this happened when CNs were insufficient to ensure plasmid transmission to descendant cells. We also found that Kid cleaved mRNA at UUACU sites, which appeared well suited to trigger a response that prevented plasmid loss and increased R1 CNs without killing cells, as suggested by our results. In view of all this, we argued that Kid and Kis functioned as a rescue system for plasmid R1, and not as a PSK system (24). This proposal cannot be supported by results elsewhere, suggesting that Kid may cleave mRNA at simpler UAH sites (with H being A, C, or U) (25, 26), a view that has prevailed in the literature (14, 16, 27–29). Moreover, other observations indicate that our past experiments may have been inappropriate to conclude that Kid does not kill Escherichia coli cells (30, 31). Importantly, Kid, Kis, and other elements that we found essential for R1 rescue are conserved in plasmids conferring resistance to extended-spectrum β-lactamases, a worrying threat to human health (1, 6–10, 32). Therapeutic options to fight pathogens carrying these plasmids are limited, and activation of Kid may be perceived as a good antibiotic alternative. Because the potential involvement of this toxin in plasmid rescue advises against such approach, we aimed to ascertain here the mode of action; the effects on cells; and, ultimately, the function of Kid (and Kis) in R1.     

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual’s recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86–0.93), whereas responses to six antigens accurately estimated an individual’s malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs.Many countries have extensive programs to reduce the burden of Plasmodium falciparum (Pf), the parasite responsible for most malaria morbidity and mortality (1). Effectively using limited resources for malaria control or elimination and evaluating interventions require accurate measurements of the risk of being infected with Pf (2–15). To reflect the rate at which individuals are infected with Pf in a useful way, metrics used to estimate exposure in a community need to account for dynamic changes over space and time, especially in response to control interventions (16–18).A variety of metrics can be used to estimate Pf exposure, but tools that are more precise and low cost are needed for population surveillance. Existing metrics have varying intrinsic levels of precision and accuracy and are subject to a variety of extrinsic factors, such as cost, time, and availability of trained personnel (19). For example, entomological measurements provide information on mosquito to human transmission for a community but are expensive, require specially trained staff, and lack standardized procedures, all of which reduce precision and/or make interpretation difficult (19–22). Parasite prevalence can be measured by detecting parasites in the blood of individuals from a cross-sectional sample of a community and is, therefore, relatively simple and inexpensive to perform, but results may be imprecise, especially in areas of low transmission (19, 23), and biased by a number of factors, including immunity and access to antimalarial treatment (5, 6, 19, 23–25). The burden of symptomatic disease in a community can be estimated from routine health systems data; however, such data are frequently unreliable (5, 26–28) and generally underestimate the prevalence of Pf infection in areas of intense transmission. Precise and quantitative information about exposure at an individual level can be reliably obtained from cohort studies by measuring the incidence of asymptomatic and/or symptomatic Pf infection (i.e., by measuring the molecular force of infection) (29–35). Unfortunately, the expense of cohort studies limits their use to research settings. The end result is that most malaria-endemic regions lack reliable, timely data on Pf exposure, limiting the capabilities of malaria control programs to guide and evaluate interventions.Serologic assays offer the potential to provide incidence estimates for symptomatic and asymptomatic Pf infection, which are currently obtained from cohort studies, at the cost of cross-sectional studies (36–38). Although Pf infections are transient, a record of infection remains detectable in an individual’s antibody profile. Thus, appropriately chosen antibody measurements integrated with age can provide information about an individual’s exposure history. Antibodies can be measured by simple ELISAs and obtained from dried blood spots, which are easy to collect, transport, and store (39–41). Serologic responses to Pf antigens have been explored as potential epidemiological tools (42–45), and estimated rates of seroconversion to well-characterized Pf antigens accurately reflect stable rates of exposure in a community, whereas distinct changes in these rates are obtained from successful interventions (22, 39, 41, 46–53). However, current serologic assays are not designed to detect short-term or gradual changes in Pf exposure or measure exposure to infection at an individual level. The ability to calibrate antibody responses to estimates of exposure in individuals could allow for more flexible sampling of a population (e.g., not requiring age stratification), improve accuracy of exposure estimates from small sample sizes, and better characterize heterogeneity in exposure within a community.Different Pf antigens elicit antibody responses with different magnitudes and kinetics, providing a large and diverse set of potential biomarkers for exposure (38, 54–58). We hypothesized that new and more highly informative serologic biomarkers better able to characterize an individual’s recent exposure history could be identified by analyzing antibody responses to a large number of candidate Pf antigens in participants with well-characterized exposure histories. To test this hypothesis, we probed plasma from participants in two cohort studies in Uganda against a protein microarray containing 856 Pf antigens. The primary aim of this analysis was to identify responses to select antigens that were most informative of recent exposure using robust, data-adaptive statistical methods. Each participant’s responses to these selected antigens were used as predictors for two primary outcomes of their recent exposure to Pf: (i) days since last Pf infection and (ii) the incidence of symptomatic malaria in the last year. These individual-level estimates were then aggregated across a population to assess community-level malaria exposure. The selection strategy presented here identified accurate biomarkers of exposure for children living in areas of moderate to high Pf exposure and illustrates the utility of this flexible and broadly applicable approach.     

Rate,spectrum, and evolutionary dynamics of spontaneous epimutations

Stochastic changes in cytosine methylation are a source of heritable epigenetic and phenotypic diversity in plants. Using the model plant Arabidopsis thaliana, we derive robust estimates of the rate at which methylation is spontaneously gained (forward epimutation) or lost (backward epimutation) at individual cytosines and construct a comprehensive picture of the epimutation landscape in this species. We demonstrate that the dynamic interplay between forward and backward epimutations is modulated by genomic context and show that subtle contextual differences have profoundly shaped patterns of methylation diversity in A. thaliana natural populations over evolutionary timescales. Theoretical arguments indicate that the epimutation rates reported here are high enough to rapidly uncouple genetic from epigenetic variation, but low enough for new epialleles to sustain long-term selection responses. Our results provide new insights into methylome evolution and its population-level consequences.Plant genomes make extensive use of cytosine methylation to control the expression of transposable elements (TEs) and genes (1). Despite its tight regulation, methylation losses or gains at individual cytosines or clusters of cytosines can emerge spontaneously, in an event termed “epimutation” (2, 3). Many examples of segregating epimutations have been documented in experimental and wild populations of plants and in some cases contribute to heritable variation in phenotypes independently of DNA sequence variation (4, 5). These observations have led to much speculation about the role of DNA methylation in plant evolution (6–8), and its potential in breeding programs (9). In the model plant Arabidopsis thaliana, spontaneous methylation changes at CG dinucleotides accumulate in a rapid but nonlinear fashion over generations (2, 3, 10), thus pointing to high forward–backward epimutation rates (11). Precise estimates of these rates are necessary to be able to quantify the long-term dynamics of epigenetic variation under laboratory or natural conditions, and to understand the molecular mechanisms that drive methylome evolution (12–14). Here we combine theoretical modeling with high-resolution methylome analysis of multiple independent A. thaliana mutation accumulation (MA) lines (15), including measurements of methylation changes in continuous generations, to obtain robust estimates of forward and backward epimutation rates.     

From the Cover: Form of an evolutionary tradeoff affects eco-evolutionary dynamics in a predator–prey system

Evolution on a time scale similar to ecological dynamics has been increasingly recognized for the last three decades. Selection mediated by ecological interactions can change heritable phenotypic variation (i.e., evolution), and evolution of traits, in turn, can affect ecological interactions. Hence, ecological and evolutionary dynamics can be tightly linked and important to predict future dynamics, but our understanding of eco-evolutionary dynamics is still in its infancy and there is a significant gap between theoretical predictions and empirical tests. Empirical studies have demonstrated that the presence of genetic variation can dramatically change ecological dynamics, whereas theoretical studies predict that eco-evolutionary dynamics depend on the details of the genetic variation, such as the form of a tradeoff among genotypes, which can be more important than the presence or absence of the genetic variation. Using a predator–prey (rotifer–algal) experimental system in laboratory microcosms, we studied how different forms of a tradeoff between prey defense and growth affect eco-evolutionary dynamics. Our experimental results show for the first time to our knowledge that different forms of the tradeoff produce remarkably divergent eco-evolutionary dynamics, including near fixation, near extinction, and coexistence of algal genotypes, with quantitatively different population dynamics. A mathematical model, parameterized from completely independent experiments, explains the observed dynamics. The results suggest that knowing the details of heritable trait variation and covariation within a population is essential for understanding how evolution and ecology will interact and what form of eco-evolutionary dynamics will result.Evolutionary dynamics, changes in intraspecific genotype frequency over generations, can have a time scale similar to that of ecological dynamics (1–3). Selection mediated by ecological interactions causes evolutionary dynamics, and evolution of traits, in turn, changes ecological interactions. Thus, understanding population dynamics needs to take account of the feedbacks between trait evolution and ecological interactions (i.e., eco-evolutionary feedbacks). These feedbacks have increasingly attracted ecologists’ attention since Pimentel (4) proposed genetic feedback as a mechanism regulating animal populations (e.g., refs. 5–11). This integration of evolutionary biology and ecology has important implications in both basic and applied problems in biology (12–17).Empirical studies have shown that rapid evolution can affect many ecological interactions, including predator–prey (18–20), host–parasite (21), herbivore–plant (22), competitive interactions (23), and interactions with abiotic environments (24–27). Previous empirical studies on eco-evolutionary feedbacks have usually compared the dynamics of populations with and without genetic variation, but recent theoretical models predicted that not only the presence or absence of genetic variation (28–30) but also the form of the evolutionary tradeoff among genotypes is important in generating qualitatively different dynamics (31–35). Indeed, the forms of evolutionary tradeoffs within populations are known to be remarkably variable in plants and microbes (36–38). Thus, there should be various eco-evolutionary dynamics depending on the form of evolutionary tradeoffs existing in wild populations. Nevertheless, to our knowledge, no empirical study has directly demonstrated the theoretically predicted effects of the evolutionary tradeoff on eco-evolutionary dynamics, and it is still unclear how different forms of an evolutionary tradeoff in real organisms can result in different eco-evolutionary dynamics.Here, using a predator–prey (rotifer–algal) system cultured in continuous flow-through microcosms (chemostats), we examined how different forms of an evolutionary tradeoff between defense and growth in algal prey (Chlorella vulgaris) affect the population dynamics of the predator–prey system and the evolutionary changes in the clonal frequency of the algal prey. Experimental studies using laboratory microcosms have been a powerful approach in exploring eco-evolutionary dynamics and testing theoretical predictions because of the constant environment and simple community structure (39–41). We used two different pairs of algal clones originally obtained from the University of Texas (UTEX) algal collection that showed different forms of a fitness tradeoff between antipredator defense and competitive ability to obtain the resource limiting population growth in the experimental system (inorganic nitrogen). Each pair of algal clones was cultured with an obligately asexual lineage of rotifer predators (Brachionus calyciflorus). Population dynamics of the predators and prey and clonal frequency changes in the algal pair were observed in long-term chemostat runs. We recorded evolutionary dynamics (genotype frequency change) by using an allele-specific quantitative PCR (AsQ-PCR) technique based on microsatellite DNA that allowed us to measure the relative abundance of algal clones (42). We also developed a mathematical model for the experimental system, based on a model of Jones and Ellner (43), parameterized the model using data from separate experiments, and compared the model’s predictions to the observed population and genotype dynamics.     

Loss of diphthamide pre-activates NF-κB and death receptor pathways and renders MCF7 cells hypersensitive to tumor necrosis factor

The diphthamide on human eukaryotic translation elongation factor 2 (eEF2) is the target of ADP ribosylating diphtheria toxin (DT) and Pseudomonas exotoxin A (PE). This modification is synthesized by seven dipthamide biosynthesis proteins (DPH1–DPH7) and is conserved among eukaryotes and archaea. We generated MCF7 breast cancer cell line-derived DPH gene knockout (ko) cells to assess the impact of complete or partial inactivation on diphthamide synthesis and toxin sensitivity, and to address the biological consequence of diphthamide deficiency. Cells with heterozygous gene inactivation still contained predominantly diphthamide-modified eEF2 and were as sensitive to PE and DT as parent cells. Thus, DPH gene copy number reduction does not affect overall diphthamide synthesis and toxin sensitivity. Complete inactivation of DPH1, DPH2, DPH4, and DPH5 generated viable cells without diphthamide. DPH1ko, DPH2ko, and DPH4ko harbored unmodified eEF2 and DPH5ko ACP- (diphthine-precursor) modified eEF2. Loss of diphthamide prevented ADP ribosylation of eEF2, rendered cells resistant to PE and DT, but does not affect sensitivity toward other protein synthesis inhibitors, such as saporin or cycloheximide. Surprisingly, cells without diphthamide (independent of which the DPH gene compromised) were presensitized toward nuclear factor of kappa light polypeptide gene enhancer in B cells (NF-κB) and death-receptor pathways without crossing lethal thresholds. In consequence, loss of diphthamide rendered cells hypersensitive toward TNF-mediated apoptosis. This finding suggests a role of diphthamide in modulating NF-κB, death receptor, or apoptosis pathways.Eukaryotic translation elongation factor 2 (eEF2) is a highly conserved protein and essential for protein biosynthesis. EEF2 enables peptide-chain elongation by translocating the peptide–tRNA complex from the A- to the P-site of the ribosome (1, 2). The diphthamide modification at His715 of human eEF2 (or at the corresponding position in other species) is conserved in all eukaryotes (3) and in archaeal counterparts. It is generated by proteins that are encoded by seven genes (4). Proteins encoded by dipthamide biosynthesis protein (DPH)1, DPH2, DPH3, and DPH4 (DNAJC24) attach a 3-amino-3-carboxypropyl (ACP) group to eEF2. This intermediate is converted by the methyltransferase DPH5 to diphthine, which is subsequently amidated to diphthamide by DPH6 and DPH7 (5).Diphthamide synthesis was previously described in yeast and other eukaryotes (4–6). However, the “complete picture” is (with the exception of the yeast pathway) to a large portion is composed of observations made in different cell types on single genes. Many reports related to diphthamide synthesis of mammalian cells describe “partial knockouts” and “partial phenotypes” (i.e., reduced levels but not complete loss of diphthamide modification or toxin sensitivities) (7–9). Because mammalian genomes are more complex than that of yeast, carrying extendend gene families, mammalian cells may compensate—at least to some degree—functional loss of genes that may be unique and essential in yeast. If and to what degree mammalian cells can compensate a partial or complete loss of DPH gene functionality (and with what consequences) is unknown to date.So far, the function of diphthamide on eEF2 also remained rather elusive. Reports indicate that it contributes to translation fidelity (10–13). On the other hand, DPH genes or eEF2 can be mutated to prevent diphthamide attachment, yet cells carrying such mutations are viable (5, 11, 14, 15). Animals with heterozygous DPH knockouts (DPHko) can be generated, but homozygous DPH1ko, DPH3ko, and DPH4ko are embryonic lethal (13, 16–18). Because these studies are based on inactivation of individual genes, it is difficult to discriminate between phenotypes caused by gene loss and phenotypes as a consequence of loss of diphthamide.Diphthamide-modified eEF2 is the target of ADP ribosylating toxins, including Pseudomonas exotoxin A (PE) and diphtheria toxin (DT) (19). These bacterial proteins enter cells and catalyze ADP ribosylation of diphthamide using nictotinamide adenine dinucleotide (NAD) as substrate (20, 21). This inactivates eEF2, arrests protein synthesis, and kills (14). Tumor-targeted PE and DT derivatives are applied in cancer therapies (22–28) and their efficacy depends on toxin sensitivity of target cells. Therefore, information about factors (and their relative contributions) that influences cellular sensitivities toward diphthamide-modifying toxins may predict therapy responses. For example, alterations in OVCA1 (human DPH1) were described for ovarian cancers (16, 29), yet it is not known if and to what degree such alterations would affect sensitivities of tumor cells toward PE-derived drugs.Here we describe MCF7 breast cancer cell line derivatives with heterozygous or complete DPH gene inactivations. These cells are applied to analyze the contributions of individual DPHs not only to diphthamide synthesis and toxin sensitivity, but also to address gene dose effects. Because the set of knockout cell lines is derived from the same parent cell and provides loss of diphthamide as common consequence of inactivation of different genes, these cells can also shed light on the biological relevance of the diphthamide modification.     

Phagocytosis genes nonautonomously promote developmental cell death in the Drosophila ovary

Programmed cell death (PCD) is usually considered a cell-autonomous suicide program, synonymous with apoptosis. Recent research has revealed that PCD is complex, with at least a dozen cell death modalities. Here, we demonstrate that the large-scale nonapoptotic developmental PCD in the Drosophila ovary occurs by an alternative cell death program where the surrounding follicle cells nonautonomously promote death of the germ line. The phagocytic machinery of the follicle cells, including Draper, cell death abnormality (Ced)-12, and c-Jun N-terminal kinase (JNK), is essential for the death and removal of germ-line–derived nurse cells during late oogenesis. Cell death events including acidification, nuclear envelope permeabilization, and DNA fragmentation of the nurse cells are impaired when phagocytosis is inhibited. Moreover, elimination of a small subset of follicle cells prevents nurse cell death and cytoplasmic dumping. Developmental PCD in the Drosophila ovary is an intriguing example of nonapoptotic, nonautonomous PCD, providing insight on the diversity of cell death mechanisms.Programmed cell death (PCD) is the genetically controlled elimination of cells that occurs during organismal development and homeostasis. Cells are considered dead when they have undergone irreversible plasma membrane permeabilization or have become completely fragmented (1). Apoptosis is the most well-characterized form of PCD, however there are at least a dozen cell death modalities that are morphologically, biochemically, and genetically distinct (2, 3). Two examples of nonapoptotic cell death are autophagic cell death and necrosis, but there are several alternative cell death mechanisms that are less well understood.Nonapoptotic PCD occurs on a large scale in the Drosophila ovary. Drosophila females can produce hundreds of eggs during their lifetime, and for every egg that is formed, developmental PCD of supporting nurse cells (NCs) occurs. However, the mechanisms of developmental PCD in the Drosophila ovary are poorly understood. Each egg forms from a 16-cell germ-line cyst, comprised of the single oocyte and 15 NCs that support the oocyte throughout 14 stages of oogenesis (4, 5). Hundreds of somatically derived follicle cells (FCs) surround the germ-line cyst, forming an egg chamber. At stage 11 of oogenesis, NCs rapidly transfer (“dump”) their cytoplasm into the oocyte. Concurrently, the NCs asynchronously undergo developmental PCD, resulting in mature stage 14 egg chambers that no longer contain any NCs (4–6). Interestingly, caspases, proteases associated with apoptosis, play only a minor role in the death of the NCs in late oogenesis (7–9). Furthermore, combined inhibition of caspases and autophagy does not significantly block NC death during late oogenesis (10). To date, defining the major mechanism of developmental PCD in the Drosophila ovary has remained elusive.An intriguing possibility is that the somatic FCs non–cell-autonomously promote developmental PCD of the NCs during late oogenesis. Non–cell-autonomous regulation of PCD occurs when a cell or group of cells extrinsically initiates or promotes the death of another cell. This concept challenges the idea that PCD is largely a self-regulated, autonomous suicide program in which a cell controls its own demise. One well-characterized example of non–cell-autonomous control of PCD is apoptosis induced by the death ligands Fas or TNF (11, 12).Another type of non–cell-autonomous PCD is phagoptosis (or primary phagocytosis), in which engulfing cells directly cause the death of other cells via “murder” or “assisted suicide.” Phagoptosis is distinct from the engulfment of cell corpses, as the engulfing cell plays an active role in the death of a cell, rather than simply degrading a cell that died via another mechanism. The defining characteristic of phagoptosis is that inhibition of phagocytosis leads to a failure in cell death (13, 14). Phagoptosis has been demonstrated in activated microglia that phagocytose viable neurons, resulting in their destruction (13–15). Entosis is another example of non–cell-autonomous PCD, often referred to as “cell cannibalism,” in which a viable cell invades another cell, where it is degraded by lysosomes. Entosis is distinct from phagoptosis, as the inhibition of phagocytosis genes does not prevent entosis (16). Phagocytosis has also been shown to promote PCD in Caenorhabditis elegans, although this is an example of assisted suicide, as dying cells also require apoptotic machinery (17, 18).Genetic studies in C. elegans have identified two partially redundant signaling pathways that control phagocytosis: the cell death abnormality (CED)-1, 6, 7 and CED-2, 5, 12 pathways (19–21). The CED-1, 6, 7 and CED-2, 5, 12 pathways act in parallel to promote the activation of CED-10, a Rac GTPase responsible for cytoskeletal rearrangements that allow for internalization of the cell corpse. In Drosophila, the roles of the Ced-1, 6, 7 and Ced-2, 5, 12 pathways appear to be conserved. The CED-1 ortholog, Draper, is a transmembrane protein that localizes to the surface of the engulfing cell and acts as a receptor to recognize dying cells. Draper was first shown to be required for engulfment of apoptotic neurons in the embryonic central nervous system with mutants displaying lingering cell corpses (22). Additionally, Draper has been shown to be important in several other contexts including the engulfment of severed axons, bacteria, imaginal disc cells, hemocytes, and apoptotic NCs in midoogenesis (23–27). In addition to Draper, other Drosophila engulfment receptors include Croquemort (28) and integrins (29–31). Croquemort is related to CD36, a scavenger receptor involved in engulfment in mammals (32), and integrins also act as engulfment receptors in C. elegans and mammals (33, 34). The upstream activators of the Ced-2, 5, 12 pathway are largely unknown, although integrins may activate the pathway (34). As in C. elegans, it appears that Ced-12 and draper function in separate pathways in Drosophila. Ced-12 and draper have been shown to function in distinct steps in axon clearance (35). In macrophages, Ced-12 has been shown to function in a separate pathway from simu, a bridging molecule that acts upstream of draper (36). A number of other engulfment genes have been identified in Drosophila, and their molecular interactions are under active investigation (36–39).Given the minor role for apoptosis and autophagic cell death during developmental PCD in the Drosophila ovary, we investigated the possibility that the FCs non–cell-autonomously promote NC death. Previously we showed that FCs of the Drosophila ovary are capable of phagoptosis in midoogenesis when phagocytosis genes are overexpressed (27), and we questioned whether phagocytosis genes might normally function to control cell death in late oogenesis. Indeed, we found that the phagocytosis genes draper and Ced-12/ELMO are required in the FCs for NC removal in late oogenesis and that they function partly in parallel. We also show that the FCs non–cell-autonomously control events associated with the death of the NCs, including nuclear envelope permeabilization, acidification, and DNA fragmentation. Furthermore, the genetic ablation of stretch FCs disrupted all cellular changes associated with developmental PCD of the NCs. Therefore, PCD of the NCs is a unique model of a naturally occurring developmental cell death program that is nonapoptotic and non–cell-autonomously controlled.