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.     

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.     

Ubiquitin systems mark pathogen-containing vacuoles as targets for host defense by guanylate binding proteins

Many microbes create and maintain pathogen-containing vacuoles (PVs) as an intracellular niche permissive for microbial growth and survival. The destruction of PVs by IFNγ-inducible guanylate binding protein (GBP) and immunity-related GTPase (IRG) host proteins is central to a successful immune response directed against numerous PV-resident pathogens. However, the mechanism by which IRGs and GBPs cooperatively detect and destroy PVs is unclear. We find that host cell priming with IFNγ prompts IRG-dependent association of Toxoplasma- and Chlamydia-containing vacuoles with ubiquitin through regulated translocation of the E3 ubiquitin ligase tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6). This initial ubiquitin labeling elicits p62-mediated escort and deposition of GBPs to PVs, thereby conferring cell-autonomous immunity. Hypervirulent strains of Toxoplasma gondii evade this process via specific rhoptry protein kinases that inhibit IRG function, resulting in blockage of downstream PV ubiquitination and GBP delivery. Our results define a ubiquitin-centered mechanism by which host cells deliver GBPs to PVs and explain how hypervirulent parasites evade GBP-mediated immunity.Pathogen-containing vacuoles (PVs) provide a safe haven to many intracellular bacterial and protozoan pathogens (1). Within the vacuolar enclosure of PVs, these pathogens can accumulate nutrients required for microbial growth. Moreover, life within the vacuolar niche shields microbes from cytoplasmic immune sensors that, once activated, can trigger proinflammatory and cell-autonomous immune responses (1). Accordingly, many intracellular pathogens such as the bacterium Chlamydia trachomatis and the protozoan Toxoplasma gondii have successfully adapted to a vacuolar lifestyle.For the host to successfully combat infections with PV-resident microbes, the innate immune system must target PVs and its inhabitants for destruction. Critical mediators of host-directed attacks on PVs are two families of IFNγ-inducible GTPases: immunity-related GTPases (IRGs) and guanylate binding proteins (GBPs) (2). Members of both GTPase families play roles in host-mediated lysis of PVs, a process resulting in the release of microbes into the host cell cytoplasm, subsequent killing of PV-expelled microbes, and host cell death (3–8). Additionally, GBPs help deliver cytosolic subunits of the antimicrobial NADPH oxidase NOX2 for assembly on phagosomal membranes, orchestrate the capture of PV-resident microbes inside degradative autophagolysosomes, and promote the activation of canonical and noncanonical inflammasome pathways (5, 8–12). As a critical first step underlying most if not all of these known GBP-controlled cell-autonomous immune responses, GBPs must locate to their intracellular microbial targets.GBPs belong to the dynamin superfamily of large GTPases (13). Similar to other members of the dynamin superfamiliy, GBPs can assemble as oligomers in a nucleotide-dependent fashion (13). Binding of GTP results in dimer formation; subsequent GTP hydrolysis prompts conformational changes that enable GBPs to assemble as tetramers (14, 15). Mutations in the G domain that reduce nucleotide binding affinities and hydrolytic activity block GBP oligomerization, constrain the localization of GBPs to the cytoplasm, and prevent GBPs from binding to PV membranes (9, 15–18). These observations support a model in which GBP monomers are diffusely distributed in the cytoplasm and GBP oligomers associate with membranes. However, these observations fail to account for the specificity with which oligomeric GBPs agglomerate on PV membranes.PVs formed by C. trachomatis and T. gondii recruit not only GBPs but also members of the IRG family of IFNγ-inducible GTPase (4, 19). The IRG protein family can be divided into two subgroups: IRGM and GKS proteins (20). Whereas GKS proteins feature the canonical glycine–lysine–serine (GKS) P-loop sequence, IRGM proteins have a substitution of a lysine for a methionine in their P-loop sequence (20). IRGM and GKS proteins also differ in their subcellular localization: IRGM proteins associate with endomembranes, whereas monomeric GDP-bound GKS proteins predominantly reside within the host cell cytoplasm (4, 17, 21, 22). Once GKS proteins transition into a GTP-bound active state, they can bind to PV membranes (21). IRGM proteins inhibit this activation step and thereby guard IRGM-decorated membranes against GKS protein targeting (17, 21). Because PV membranes surrounding either C. trachomatis or T. gondii are largely devoid of IRGM proteins, they are the preferred GKS binding substrate following a “missing-self” principle of immune targeting (17, 23). In IRGM-deficient cells, however, GKS proteins enter the active state prematurely, form protein aggregates, mislocalize, and thus fail to bind to PVs (17, 21). Although these previous observations help explain how IRGM proteins promote the delivery of GKS proteins to PVs, IRGM proteins also control the subcellular localization of GBPs through an uncharacterized mechanism (6, 17, 24–26).Here, we report a previously unidentified host-directed ubiquitination pathway involved in innate immunity. We demonstrate that Chlamydia- and Toxoplasma-containing vacuoles become ubiquitin-decorated upon IFNγ priming of their host cells. IFNγ-dependent association of ubiquitin with PVs requires IFNγ-inducible IRG proteins and the E3 ligase tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6). Experimental removal of the IFNγ-inducible ubiquitination pathway dramatically diminishes the p62-dependent delivery of GBPs to PVs and thereby renders host cells more susceptible to infections. Thus, our observations imply that ubiquitin serves as a host-induced pattern that marks intracellular structures as immune targets for members of the GBP family of host defense proteins.     

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.     

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.     

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.     

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.     

Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory

Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β′1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts.Although forgetting commonly has a negative connotation, it is a functional process that shapes memory and cognition (1–4). Recent studies, including work in relatively simple invertebrate models, have started to reveal basic biological mechanisms underlying forgetting (5–15). In Drosophila, single-session Pavlovian conditioning by pairing an odor (conditioned stimulus, CS) with electric shock (unconditioned stimulus, US) induces aversive memories that are short-lasting (16). The memory performance of fruit flies is observed to drop to a negligible level within 24 h, decaying rapidly early after training and slowing down thereafter (17). Memory decay or forgetting requires the activation of the small G protein Rac, a signaling protein involved in actin remodeling, in the mushroom body (MB) intrinsic neurons (6). These so-called Kenyon cells (KCs) are the neurons that integrate CS–US information (18, 19) and support aversive memory formation and retrieval (20–22). In addition to Rac, forgetting also requires the DAMB dopamine receptor (7), which has highly enriched expression in the MB (23). Evidence suggests that the dopamine-mediated forgetting signal is conveyed to the MB by dopamine neurons (DANs) in the protocerebral posterior lateral 1 (PPL1) cluster (7, 24). Therefore, forgetting of olfactory aversive memory in Drosophila depends on a particular set of intracellular molecular pathways within KCs, involving Rac, DAMB, and possibly others (25), and also receives modulation from extrinsic neurons. Although important cellular evidence supporting the hypothesis that memory traces are erased under these circumstances is still lacking, these findings lend support to the notion that forgetting is an active, biologically regulated process (17, 26).Although existing studies point to the MB circuit as essential for forgetting, several questions remain to be answered. First, whereas the molecular pathways for learning and forgetting of olfactory aversive memory are distinct and separable (6, 7), the neural circuits seem to overlap. Rac-mediated forgetting has been localized to a large population of KCs (6), including the γ-subset, which is also critical for initial memory formation (21, 27). The site of action of DAMB for forgetting has yet to be established; however, the subgroups of PPL1-DANs implicated in forgetting are the same as those that signal aversive reinforcement and are required for learning (28–30). It leaves open the question of whether the brain circuitry underlying forgetting and learning is dissociable, or whether forgetting and learning share the same circuit but are driven by distinct activity patterns and molecular machinery (26). Second, shock reinforcement elicits multiple memory traces through at least three dopamine pathways to different subdomains in the MB lobes (28, 29). Functional imaging studies have also revealed Ca²⁺-based memory traces in different KC populations (31). It is poorly understood how forgetting of these memory traces differs, and it remains unknown whether there are multiple regulatory neural pathways. Notably, when PPL1-DANs are inactivated, forgetting still occurs, albeit at a lower rate (7). This incomplete block suggests the existence of an additional pathway(s) that conveys forgetting signals to the MB. Third, other than memory decay over time, forgetting is also observed through interference (32, 33), when new learning or reversal learning is introduced after training (6, 34, 35). Time-based and interference-based forgetting shares a similar dependence on Rac and DAMB (6, 7). However, it is not known whether distinct circuits underlie forgetting in these different contexts.In the current study, we focus on the diverse set of MB extrinsic neurons (MBENs) that interconnect the MB lobes with other brain regions, which include 34 MB output neurons (MBONs) of 21 types and ∼130 dopaminergic neurons of 20 types in the PPL1 and protocerebral anterior medial (PAM) clusters (36, 37). These neurons have been intensively studied in olfactory memory formation, consolidation, and retrieval in recent years (e.g., 24, 28–30, 38–48); however, their roles in forgetting have not been characterized except for the aforementioned PPL1-DANs. In a functional screen, we unexpectedly found that several Gal4 driver lines of MBENs showed significantly better 3-h memory retention when the Gal4-expressing cells were inactivated. The screen has thus led us to identify two types of MBENs that are not involved in initial learning but play important and additive roles in mediating memory decay. Furthermore, neither of these MBEN types is required for reversal learning, supporting the notion that there is a diversity of neural circuits that drive different forms of forgetting.