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.     

Hyperpolarization-activated,cyclic nucleotide-gated cation channels in Aplysia: Contribution to classical conditioning

Hyperpolarization-activated, cyclic nucleotide-gated cation (HCN) channels are critical regulators of neuronal excitability, but less is known about their possible roles in synaptic plasticity and memory circuits. Here, we characterized the HCN gene organization, channel properties, distribution, and involvement in associative and nonassociative forms of learning in Aplysia californica. Aplysia has only one HCN gene, which codes for a channel that has many similarities to the mammalian HCN channel. The cloned acHCN gene was expressed in Xenopus oocytes, which displayed a hyperpolarization-induced inward current that was enhanced by cGMP as well as cAMP. Similarly to its homologs in other animals, acHCN is permeable to K⁺ and Na⁺ ions, and is selectively blocked by Cs⁺ and ZD7288. We found that acHCN is predominantly expressed in inter- and motor neurons, including LFS siphon motor neurons, and therefore tested whether HCN channels are involved in simple forms of learning of the siphon-withdrawal reflex in a semiintact preparation. ZD7288 (100 μM) significantly reduced an associative form of learning (classical conditioning) but had no effect on two nonassociative forms of learning (intermediate-term sensitization and unpaired training) or baseline responses. The HCN current is enhanced by nitric oxide (NO), which may explain the postsynaptic role of NO during conditioning. HCN current in turn enhances the NMDA-like current in the motor neurons, suggesting that HCN channels contribute to conditioning through this pathway.Hyperpolarization-activated, cyclic nucleotide-gated (HCN), cation nonselective ion channels generate hyperpolarization-activated inward currents (I_h) and thus tend to stabilize membrane potential (1–3). In addition, binding of cyclic nucleotides (cAMP and cGMP) to the C-terminal cyclic nucleotide binding domain (CNBD) enhances I_h and thus couples membrane excitability with intracellular signaling pathways (2, 4). HCN channels are widely important for numerous systemic functions such as hormonal regulation, heart contractility, epilepsy, pain, central pattern generation, sensory perception (4–15), and learning and memory (16–24).However, in previous studies it has been difficult to relate the cellular effects of HCN channels directly to their behavioral effects, because of the immense complexity of the mammalian brain. We have therefore investigated the role of HCN channels in Aplysia, which has a numerically simpler nervous system (25). We first identified and characterized an HCN gene in Aplysia, and showed that it codes for a channel that has many similarities to the mammalian HCN channel. We found that the Aplysia HCN channel is predominantly expressed in motor neurons including LFS neurons in the siphon withdrawal reflex circuit (26, 27). We therefore investigated simple forms of learning of that reflex in a semiintact preparation (28–30) and found that HCN current is involved in classical conditioning and enhances the NMDA-like current in the motor neurons. These results provide a direct connection between HCN channels and behavioral learning and suggest a postsynaptic mechanism of that effect. HCN current in turn is enhanced by nitric oxide (NO), a transmitter of facilitatory interneurons, and thus may contribute to the postsynaptic role of NO during conditioning.     

Neural substrate for higher-order learning in an insect: Mushroom bodies are necessary for configural discriminations

Learning theories distinguish elemental from configural learning based on their different complexity. Although the former relies on simple and unambiguous links between the learned events, the latter deals with ambiguous discriminations in which conjunctive representations of events are learned as being different from their elements. In mammals, configural learning is mediated by brain areas that are either dispensable or partially involved in elemental learning. We studied whether the insect brain follows the same principles and addressed this question in the honey bee, the only insect in which configural learning has been demonstrated. We used a combination of conditioning protocols, disruption of neural activity, and optophysiological recording of olfactory circuits in the bee brain to determine whether mushroom bodies (MBs), brain structures that are essential for memory storage and retrieval, are equally necessary for configural and elemental olfactory learning. We show that bees with anesthetized MBs distinguish odors and learn elemental olfactory discriminations but not configural ones, such as positive and negative patterning. Inhibition of GABAergic signaling in the MB calyces, but not in the lobes, impairs patterning discrimination, thus suggesting a requirement of GABAergic feedback neurons from the lobes to the calyces for nonelemental learning. These results uncover a previously unidentified role for MBs besides memory storage and retrieval: namely, their implication in the acquisition of ambiguous discrimination problems. Thus, in insects as in mammals, specific brain regions are recruited when the ambiguity of learning tasks increases, a fact that reveals similarities in the neural processes underlying the elucidation of ambiguous tasks across species.Learning can be categorized into two levels of complexity termed elemental and configural (nonelemental) (1–3). Simple and unambiguous links between events characterize elemental learning (4). By contrast, ambiguity and nonlinearity characterize configural learning, where associations involve conjunctions of elemental stimuli, which may have different, contradictory outcomes. As a consequence, solving configural tasks typically requires treating stimulus conjunctions as being different from the simple sum of their elemental components (5–8). For example, in a negative patterning task (9–11), subjects have to discriminate a nonreinforced conjunction of two elements A and B from its reinforced elements (i.e., AB– vs. A+ and B+), which requires treating AB as being different from the simple sum of A and B (12, 13). The ambiguity of the task lies in the fact that each element (A and B) is as often reinforced (when presented alone) as nonreinforced (when presented as a compound). In mammals, different brain structures have been associated with these two learning forms: Whereas the hippocampus seems to be dispensable for learning elemental associations (6, 8), it is required for fast formation of conjunctive representations during learning tasks, such as spatial learning or contextual fear conditioning (6, 8, 10, 14–19). Moreover, the cortical system is necessary to form configural representations over extended training, thus supporting the learning of nonlinear discriminations,Here, we ask whether the specialization of different brain centers for learning tasks of different complexity is a property that can be extended to an insect brain. Insects offer the possibility of studying sophisticated behaviors and simultaneously accessing the neural bases of these behaviors (20). Several studies have shown that insects, in particular the honey bee Apis mellifera, possess higher-order cognitive abilities (5, 21), which raises the question of which neural mechanisms support these capacities in a brain whose size is only 1 mm³ (22).The mushroom bodies (MBs) are paired structures in the insect brain that have been historically associated with olfactory learning and memory. Their function has been extensively studied in a variety of elemental learning protocols, mainly in the honey bee and the fruit fly Drosophila melanogaster (23–29). In both species, MBs play a fundamental role for the encoding, storing, and retrieval of appetitive and aversive elemental memories, but no study has clearly established their role for nonelemental learning and memory (30). In fruit flies, this missing information may be due to the incapacity of these insects to solve nonelemental problems, such as negative patterning (31). By contrast, honey bees exhibit elaborated nonelemental learning abilities (32–36), which have been suggested to require intact MB function (5).Here, we used a combination of nonelemental conditioning protocols, disruption of MB function, and optophysiological recordings of neural activity to determine whether MBs are necessary for nonelemental forms of learning. Our results show that acquisition of olfactory patterning discriminations is impaired in bees in which neural activity in the MBs was blocked by procaine injection (37, 38), but not in control animals injected with saline solution. By contrast, MB blockade by procaine affected neither olfactory processing upstream of the MBs nor elemental olfactory discriminations. To uncover the neural mechanisms underlying the necessity of MBs for patterning discriminations, we focused on GABAergic feedback neurons (39), which provide inhibitory feedback to the MBs of the bee (40–43). We blocked GABAergic signaling by locally injecting picrotoxin (PTX), a GABA antagonist, into the MB calyces or into the MB lobes. We show that GABAergic feedback to the calyces—but not to the lobes—is required for patterning discriminations. These results uncover a previously unidentified role for MBs: namely, the disambiguation between elemental and conjunctive odor representations, thus supporting the learning of nonlinear discriminations.     

From the Cover: PNAS Plus: Whole-brain calcium imaging with cellular resolution in freely behaving Caenorhabditis elegans

The ability to acquire large-scale recordings of neuronal activity in awake and unrestrained animals is needed to provide new insights into how populations of neurons generate animal behavior. We present an instrument capable of recording intracellular calcium transients from the majority of neurons in the head of a freely behaving Caenorhabditis elegans with cellular resolution while simultaneously recording the animal’s position, posture, and locomotion. This instrument provides whole-brain imaging with cellular resolution in an unrestrained and behaving animal. We use spinning-disk confocal microscopy to capture 3D volumetric fluorescent images of neurons expressing the calcium indicator GCaMP6s at 6 head-volumes/s. A suite of three cameras monitor neuronal fluorescence and the animal’s position and orientation. Custom software tracks the 3D position of the animal’s head in real time and two feedback loops adjust a motorized stage and objective to keep the animal’s head within the field of view as the animal roams freely. We observe calcium transients from up to 77 neurons for over 4 min and correlate this activity with the animal’s behavior. We characterize noise in the system due to animal motion and show that, across worms, multiple neurons show significant correlations with modes of behavior corresponding to forward, backward, and turning locomotion.How do patterns of neural activity generate an animal’s behavior? To answer this question, it is important to develop new methods for recording from large populations of neurons in animals as they move and behave freely. The collective activity of many individual neurons appears to be critical for generating behaviors including arm reach in primates (1), song production in zebrafinch (2), the choice between swimming or crawling in leech (3), and decision-making in mice during navigation (4). New methods for recording from larger populations of neurons in unrestrained animals are needed to better understand neural coding of these behaviors and neural control of behavior more generally.Calcium imaging has emerged as a promising technique for recording dynamics from populations of neurons. Calcium-sensitive proteins are used to visualize changes in intracellular calcium levels in neurons in vivo which serve as a proxy for neural activity (5). To resolve the often weak fluorescent signal of an individual neuron in a dense forest of other labeled cells requires a high magnification objective with a large numerical aperture that, consequently, can image only a small field of view. Calcium imaging has traditionally been performed on animals that are stationary from anesthetization or immobilization to avoid imaging artifacts induced by animal motion. As a result, calcium imaging studies have historically focused on small brain regions in immobile animals that exhibit little or no behavior (6).No previous neurophysiological study has attained whole-brain imaging with cellular resolution in a freely behaving unrestrained animal. Previous whole-brain cellular resolution calcium imaging studies of populations of neurons that involve behavior investigate either fictive locomotion (3, 7), or behaviors that can be performed in restrained animals, such as eye movements (8) or navigation of a virtual environment (9). One exception has been the development of fluorescence endoscopy, which allows recording from rodents during unrestrained behavior, although imaging is restricted to even smaller subbrain regions (10).Investigating neural activity in small transparent organisms allows one to move beyond studying subbrain regions to record dynamics from entire brains with cellular resolution. Whole-brain imaging was performed first in larval zebrafish using two-photon microscopy (7). More recently, whole-brain imaging was performed in Caenorhabditis elegans using two-photon (11) and light-field microscopy (12). Animals in these studies were immobilized, anesthetized, or both and thus exhibited no gross behavior.C. elegans’ compact nervous system of only 302 neurons and small size of only 1 mm make it ideally suited for the development of new whole-brain imaging techniques for studying behavior. There is a long and rich history of studying and quantifying the behavior of freely moving C. elegans dating back to the mid-1970s (13, 14). Many of these works involved quantifying animal body posture as the worm moved, for example as in ref. 15. To facilitate higher-throughput recordings of behavior, a number of tracking microscopes (16–18) or multiworm imagers were developed (19, 20) along with sophisticated behavioral analysis software and analytical tools (21, 22). Motivated in part to understand these behaviors, calcium imaging systems were also developed that could probe neural activity in at first partially immobilized (23) and then freely moving animals, beginning with ref. 24 and and then developing rapidly (17, 18, 25–29). One limitation of these freely moving calcium imaging systems is that they are limited to imaging only a very small subset of neurons and lack the ability to distinguish neurons that lie atop one another in the axial direction of the microscope. Despite this limitation, these studies, combined with laser-ablation experiments, have identified a number of neurons that correlate or affect changes in particular behaviors including the AVB neuron pair and VB-type motor neurons for forward locomotion; the AVA, AIB, and AVE neuron pairs and VA-type motor neurons for backward locomotion; and the RIV, RIB, and SMD neurons and the DD-type motor neurons for turning behaviors (17, 18, 25, 26, 28, 30, 31). To move beyond these largely single-cell studies, we sought to record simultaneously from the entire brain of C. elegans with cellular resolution and record its behavior as it moved about unrestrained.     

α-Synuclein assembles into higher-order multimers upon membrane binding to promote SNARE complex formation

Physiologically, α-synuclein chaperones soluble NSF attachment protein receptor (SNARE) complex assembly and may also perform other functions; pathologically, in contrast, α-synuclein misfolds into neurotoxic aggregates that mediate neurodegeneration and propagate between neurons. In neurons, α-synuclein exists in an equilibrium between cytosolic and membrane-bound states. Cytosolic α-synuclein appears to be natively unfolded, whereas membrane-bound α-synuclein adopts an α-helical conformation. Although the majority of studies showed that cytosolic α-synuclein is monomeric, it is unknown whether membrane-bound α-synuclein is also monomeric, and whether chaperoning of SNARE complex assembly by α-synuclein involves its cytosolic or membrane-bound state. Here, we show using chemical cross-linking and fluorescence resonance energy transfer (FRET) that α-synuclein multimerizes into large homomeric complexes upon membrane binding. The FRET experiments indicated that the multimers of membrane-bound α-synuclein exhibit defined intermolecular contacts, suggesting an ordered array. Moreover, we demonstrate that α-synuclein promotes SNARE complex assembly at the presynaptic plasma membrane in its multimeric membrane-bound state, but not in its monomeric cytosolic state. Our data delineate a folding pathway for α-synuclein that ranges from a monomeric, natively unfolded form in cytosol to a physiologically functional, multimeric form upon membrane binding, and show that only the latter but not the former acts as a SNARE complex chaperone at the presynaptic terminal, and may protect against neurodegeneration.α-Synuclein is an abundant presynaptic protein that physiologically acts to promote soluble NSF attachment protein receptor (SNARE) complex assembly in vitro and in vivo (1–3). Point mutations in α-synuclein (A30P, E46K, H50Q, G51D, and A53T) as well as α-synuclein gene duplications and triplications produce early-onset Parkinson''s disease (PD) (4–10). Moreover, α-synuclein is a major component of intracellular protein aggregates called Lewy bodies, which are pathological hallmarks of neurodegenerative disorders such as PD, Lewy body dementia, and multiple system atrophy (11–14). Strikingly, neurotoxic α-synuclein aggregates propagate between neurons during neurodegeneration, suggesting that such α-synuclein aggregates are not only intrinsically neurotoxic but also nucleate additional fibrillization (15–18).α-Synuclein is highly concentrated in presynaptic terminals where α-synuclein exists in an equilibrium between a soluble and a membrane-bound state, and is associated with synaptic vesicles (19–22). The labile association of α-synuclein with membranes (23, 24) suggests that binding of α-synuclein to synaptic vesicles, and its dissociation from these vesicles, may regulate its physiological function. Membrane-bound α-synuclein assumes an α-helical conformation (25–32), whereas cytosolic α-synuclein is natively unfolded and monomeric (refs. 25, 26, 31, and 32; however, see refs. 33 and 34 and Discussion for a divergent view). Membrane binding by α-synuclein is likely physiologically important because in in vitro experiments, α-synuclein remodels membranes (35, 36), influences lipid packing (37, 38), and induces vesicle clustering (39). Moreover, membranes were found to be important for the neuropathological effects of α-synuclein (40–44).However, the relation of membrane binding to the in vivo function of α-synuclein remains unexplored, and it is unknown whether α-synuclein binds to membranes as a monomer or oligomer. Thus, in the present study we have investigated the nature of the membrane-bound state of α-synuclein and its relation to its physiological function in SNARE complex assembly. We found that soluble monomeric α-synuclein assembles into higher-order multimers upon membrane binding and that membrane binding of α-synuclein is required for its physiological activity in promoting SNARE complex assembly at the synapse.     

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.     

Short and long-lasting behavioral consequences of agonistic encounters between male Drosophila melanogaster

In many animal species, learning and memory have been found to play important roles in regulating intra- and interspecific behavioral interactions in varying environments. In such contexts, aggression is commonly used to obtain desired resources. Previous defeats or victories during aggressive interactions have been shown to influence the outcome of later contests, revealing loser and winner effects. In this study, we asked whether short- and/or long-term behavioral consequences accompany victories and defeats in dyadic pairings between male Drosophila melanogaster and how long those effects remain. The results demonstrated that single fights induced important behavioral changes in both combatants and resulted in the formation of short-term loser and winner effects. These decayed over several hours, with the duration depending on the level of familiarity of the opponents. Repeated defeats induced a long-lasting loser effect that was dependent on de novo protein synthesis, whereas repeated victories had no long-term behavioral consequences. This suggests that separate mechanisms govern the formation of loser and winner effects. These studies aim to lay a foundation for future investigations exploring the molecular mechanisms and circuitry underlying the nervous system changes induced by winning and losing bouts during agonistic encounters.Across the animal kingdom, aggression between conspecifics often accompanies the competition for food, mates, and territory. Although an innate behavior, aggression is a highly adaptive trait as well, with animals learning from previous experience and changing their behavior in response to new challenges. In competition for rank, for example, previous fighting experience influences the outcome of subsequent contests: prior defeat decreases whereas prior victory increases the probability of winning later contests. These have been called “loser” and “winner” effects (1). Such effects have been observed in many species, including fish (2), birds (3), and mammals (4). In general, loser effects persist longer than winner effects (5). The durational asymmetry observed between loser and winner effects has been hypothesized to participate in stabilizing social hierarchies among conspecifics (6).Fruit flies (Drosophila melanogaster) exhibit a variety of simple and complex social behaviors, including aggregation (7), courtship (8), and aggression (9) in which learning and memory have been demonstrated or postulated to serve important roles (10–12). Thus, characterizing the molecular basis of memory formation, retention, and retrieval is crucial to ultimately understanding the adaptability of these social behaviors. In Drosophila, a variety of operant and classical training paradigms have been used to subdivide memory into distinct categories. Short-term memory (STM) lasting minutes to hours is induced by a single training session, whereas long-term memory (LTM) lasting days usually requires repeated training sessions and involves de novo protein synthesis (13). A large number of studies have been carried out using olfactory, visual, social, and place memory paradigms. These have allowed the functional and molecular characterization of neuronal circuits and the identification of numerous genes underlying learning and memory (14–16). Included are mutations in rutabaga (rut, type 1 adenylyl cyclase) that interfere with learning and STM formation (17); amnesiac (amn, peptide regulator of adenylyl cyclase) that affect STM retention (18); and crammer (cer, inhibitor of a cathepsin subfamily) that prevent LTM formation (19). Whether rut, amn, and cer serve roles in the learning and memory that accompanies aggression remains unknown.Male–male aggression in fruit flies was first described almost 100 y ago (20). Since then, considerable progress has been made in understanding its expression and regulation (21–26). In competition for food resources and territory, male–male agonistic encounters, composed of stereotyped behavioral patterns, usually result in the formation of dominance relationships (9). During the progression of fights, both flies modify their fighting strategies: The ultimate winners chase and lunge at their opponents to gain sole access to the resources, whereas the losers retreat from the resources after receiving such attacks (9, 10).In second fights (30 min after first fights), losing flies display greater submissive behavior and never win against naïve or experienced opponents, revealing short-term loser effects (10). Evidence for winner effects, however, was not found (11). Recently, in olive fruit flies (Bactrocera olea) it was found that previous losing and winning experiences both increased the aggressiveness of the flies. This suggests that the consequences of losing or winning may vary across species (27).We previously suggested that fights between male flies function as operant learning situations in which males learn to use their most advantageous fighting strategy during fights and then continue to do so in subsequent contests (28). In an attempt to optimize the learning and memory associated with aggression, we designed new “handling-free” behavioral chambers (29). These proved to be more desirable for studying the formation of loser effects (12). By using these experimental arenas and pairing familiar opponents in second fights we previously showed that changes in fighting strategies could be developed by both winning and losing flies. This allowed us to suggest the existence of short-term winner effects along with the previously demonstrated loser effects (12). A more detailed examination of these short-term effects is presented here along with experiments attempting to measure the intrinsic changes in fighting abilities of losing and winning flies.In the present study, we ask (i) whether a single fight can lead to the formation of loser and winner effects and how long these effects persist, (ii) whether flies adopt different fighting strategies in second fights depending on their opponents, (iii) whether longer-lasting behavioral effects result from sequential repeated defeats or victories, (iv) whether protein synthesis is required for the short- or long-term effects observed, and (v) whether mutations in genes involved in learning and memory affect aggressive behavior.     

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.     

Local generation of multineuronal spike sequences in the hippocampal CA1 region

Sequential activity of multineuronal spiking can be observed during theta and high-frequency ripple oscillations in the hippocampal CA1 region and is linked to experience, but the mechanisms underlying such sequences are unknown. We compared multineuronal spiking during theta oscillations, spontaneous ripples, and focal optically induced high-frequency oscillations (“synthetic” ripples) in freely moving mice. Firing rates and rate modulations of individual neurons, and multineuronal sequences of pyramidal cell and interneuron spiking, were correlated during theta oscillations, spontaneous ripples, and synthetic ripples. Interneuron spiking was crucial for sequence consistency. These results suggest that participation of single neurons and their sequential order in population events are not strictly determined by extrinsic inputs but also influenced by local-circuit properties, including synapses between local neurons and single-neuron biophysics.A hypothesized hallmark of cognition is self-organized sequential activation of neuronal assemblies (1). Self-organized neuronal sequences have been observed in several cortical structures (2–5) and neuronal models (6–7). In the hippocampus, sequential activity of place cells (8) may be induced by external landmarks perceived by the animal during spatial navigation (9) and conveyed to CA1 by the upstream CA3 region or layer 3 of the entorhinal cortex (10). Internally generated sequences have been also described in CA1 during theta oscillations in memory tasks (4, 11), raising the possibility that a given neuronal substrate is responsible for generating sequences at multiple time scales. The extensive recurrent excitatory collateral system of the CA3 region has been postulated to be critical in this process (4, 7, 12, 13).The sequential activity of place cells is “replayed” during sharp waves (SPW) in a temporally compressed form compared with rate modulation of place cells (14–20) and may arise from the CA3 recurrent excitatory networks during immobility and slow wave sleep. The SPW-related convergent depolarization of CA1 neurons gives rise to a local, fast oscillatory event in the CA1 region (“ripple,” 140–180 Hz; refs. 8 and 21). Selective elimination of ripples during or after learning impairs memory performance (22–24), suggesting that SPW ripple-related replay assists memory consolidation (12, 13). Although the local origin of the ripple oscillations is well demonstrated (25, 26), it has been tacitly assumed that the ripple-associated, sequentially ordered firing of CA1 neurons is synaptically driven by the upstream CA3 cell assemblies (12, 15), largely because excitatory recurrent collaterals in the CA1 region are sparse (27). However, sequential activity may also emerge by local mechanisms, patterned by the different biophysical properties of CA1 pyramidal cells and their interactions with local interneurons, which discharge at different times during a ripple (28–30). A putative function of the rich variety of interneurons is temporal organization of principal cell spiking (29–32). We tested the “local-circuit” hypothesis by comparing the probability of participation and sequential firing of CA1 neurons during theta oscillations, natural spontaneous ripple events, and “synthetic” ripples induced by local optogenetic activation of pyramidal neurons.     

Dopamine-associated cached values are not sufficient as the basis for action selection

Phasic dopamine transmission is posited to act as a critical teaching signal that updates the stored (or “cached”) values assigned to reward-predictive stimuli and actions. It is widely hypothesized that these cached values determine the selection among multiple courses of action, a premise that has provided a foundation for contemporary theories of decision making. In the current work we used fast-scan cyclic voltammetry to probe dopamine-associated cached values from cue-evoked dopamine release in the nucleus accumbens of rats performing cost–benefit decision-making paradigms to evaluate critically the relationship between dopamine-associated cached values and preferences. By manipulating the amount of effort required to obtain rewards of different sizes, we were able to bias rats toward preferring an option yielding a high-value reward in some sessions and toward instead preferring an option yielding a low-value reward in others. Therefore, this approach permitted the investigation of dopamine-associated cached values in a context in which reward magnitude and subjective preference were dissociated. We observed greater cue-evoked mesolimbic dopamine release to options yielding the high-value reward even when rats preferred the option yielding the low-value reward. This result identifies a clear mismatch between the ordinal utility of the available options and the rank ordering of their cached values, thereby providing robust evidence that dopamine-associated cached values cannot be the sole determinant of choices in simple economic decision making.In contemporary theories of economic decision making, values are assigned to reward-predictive states in which animals can take action to obtain rewards, and these state-action values are stored (“cached”) for the purpose of guiding future choices based upon their rank order (1–5). It is believed that these cached values are represented as synaptic weights within corticostriatal circuitry, reflected in the activity of subpopulations of striatal projection neurons (6–9), and are updated by dopamine-dependent synaptic plasticity (10–12). Indeed, a wealth of evidence suggests that the phasic activity of dopamine neurons reports instances in which current reward or expectation of future reward differs from current expectations (13–24). This pattern of activity resembles the prediction-error term from temporal-difference reinforcement-learning algorithms, which is considered the critical teaching signal for updating cached values. A notable feature of models that integrate dopamine transmission into this computational framework is that the cached value of an action is explicitly read out by the phasic dopamine response to the unexpected presentation of a cue that designates the transition into a state in which that action yields reward. Therefore, cue-evoked dopamine signaling provides a neural representation of the cached values of available actions, and if these cached values serve as the basis for action selection, then cue-evoked dopamine responses should be rank ordered in a manner that is consistent with animals’ behavioral preferences.Numerous studies that recorded cue-evoked dopamine signaling have reported correlations with the expected utility (subjective value) of actions (24–36). For example, risk-preferring rats demonstrated greater cue-evoked dopamine release for a risky option than for a certain option with equivalent objective expected value (reward magnitude times probability), whereas risk-averse rats showed greater dopamine release for the certain than for the risky option (30). Likewise, the cached values reported by dopamine neurons in macaque monkeys accounted for individual monkeys’ subjective flavor and risk preferences, with each attribute weighted according to its influence on behavioral preferences (31, 32). These observations, which are consistent across measures of dopamine neuronal activity and dopamine release, reinforce the prevailing notion that the dopamine-associated cached values could be the primary determinant of decision making (2–5, 17, 28–32) because the cue-evoked dopamine responses were rank ordered according to the animals’ subjective preferences. However, there have been some reports that other economic attributes, such as effortful response costs (35–38) or the overt aversiveness of an outcome (39), are represented inconsistently by cue-evoked dopamine responses. For example, Gan et al. (35) showed that independent manipulations of two different dimensions (reward magnitude and effort) that had equivalent effects on behavior did not have equivalent effects on dopamine release. Paralleling these findings, a recent report reached a similar conclusion that dopamine transmission preferentially encodes an appetitive dimension but is relatively insensitive to aversiveness (39).Because these cue-evoked dopamine signals represent cached values that are purported to determine action selection, their differential encoding of economic dimensions has potentially problematic implications in the context of decision making. Namely, by extrapolating from these studies (35–39), one might infer that when a decision involves the tradeoff between these economic dimensions, the rank order of the dopamine-associated cached values for each of the available options would not consistently reflect the ordinal utility of these options and therefore these cached values could not, on their own, be the basis of choices. However, this counterintuitive prediction was not tested explicitly by any of these previous studies; thus it remains a provocative notion that merits direct examination, because it is contrary to the prevailing hypothesis described above which is fundamental to contemporary theories of decision making. Therefore, we investigated interactions between dimensions that previously have been shown during independent manipulations to be weakly or strongly incorporated into these cached values. Specifically, we increased the amount of effort required to obtain a large reward so that animals instead preferred a low-effort option yielding a smaller reward, and we used fast-scan cyclic voltammetry to record cue-evoked mesolimbic dopamine release as a neurochemical proxy for each option’s cached value. These conditions permitted us to test whether the cached values reported via cue-evoked dopamine indeed align with animals’ subjective preferences across these mixed cost–benefit attributes.     

Orexin/hypocretin system modulates amygdala-dependent threat learning through the locus coeruleus

Survival in a dangerous environment requires learning about stimuli that predict harm. Although recent work has focused on the amygdala as the locus of aversive memory formation, the hypothalamus has long been implicated in emotional regulation, and the hypothalamic neuropeptide orexin (hypocretin) is involved in anxiety states and arousal. Nevertheless, little is known about the role of orexin in aversive memory formation. Using a combination of behavioral pharmacology, slice physiology, and optogenetic techniques, we show that orexin acts upstream of the amygdala via the noradrenergic locus coeruleus to enable threat (fear) learning, specifically during the aversive event. Our results are consistent with clinical studies linking orexin levels to aversive learning and anxiety in humans and dysregulation of the orexin system may contribute to the etiology of fear and anxiety disorders.Hess and Akert demonstrated that electrical stimulation of the perifornical (PFH) region of the hypothalamus elicits defensive or aggressive responses in cats (1). Others showed that hypothalamic stimulation can serve as the aversive unconditioned stimulus (US) (2), indicating that the hypothalamus processes threat information important for aversive learning. One possibility is that orexin neurons, which populate these hypothalamic areas, may mediate these observed responses, as these neurons project to and modulate brain areas critical for threat processing, reward, and memory.Orexins are neuropeptides produced in the PFH and lateral regions of the hypothalamus (LH) (3, 4). Two orexin peptides (Orexin-A and Orexin-B) are processed from one peptide precursor (prepro-orexin) and bind two distinct G protein–coupled receptors (OrxR1 and OrxR2) in the brain (3, 4). Activation of either receptor commonly increases excitability in target neurons by reducing potassium channel conductance, enhancing presynaptic glutamate release, or increasing postsynaptic NMDA receptor (NMDAR) conductance (5, 6). Orexin receptors are differentially distributed in the brain and may serve differing roles in stress, arousal, vigilance, feeding, reward processing, and drug addiction (7–10). Evidence suggests that, in general, OrxR2 is involved in maintenance of arousal or wakefulness (11, 12), whereas OrxR1 mediates responses to environmental stimuli (13, 14).Recent reports point to a role for the orexin system in emotional regulation. Overactivity in orexin neurons can exacerbate panic-like episodes and lead to an anxiety-like phenotype in rats (15, 16). Conversely, administration of the dual orexin receptor antagonist almorexant blunts autonomic and behavioral responses affiliated with heightened stress levels (17, 18). Although orexin system activity is linked to general states of hyperarousal, the precise role of orexin in these and other aversive states remains unknown.Hypothalamic orexin neurons send a dense output to the locus coeruelus (LC) and depolarize neurons in vitro and in vivo (19–21). In line with their connectivity, LC neurons respond to phasic stimuli in a manner comparable to orexin neurons (22), suggesting that orexin neurons modulate LC responses to salient sensory events. Interestingly, orexin and LC neurons are both activated by aversive stimuli such as shock (23, 24). Thus, orexin could contribute to aversive learning by way of LC, given the importance of norepinephrine to aversive memory processes in amygdala (25–27).Pavlovian threat (fear) conditioning is a well-established behavioral paradigm to assess the formation, storage, and expression of aversive memories (28). During training, animals learn to associate an aversive US, such as a footshock, with a neutral conditioned stimulus (CS), such as a tone, when both occur in close temporal proximity. Here, we tested the hypothesis that orexin neurons phasically activate locus coeruleus neurons during an aversive event to enable threat learning. Using a combination of behavioral pharmacology, electrophysiology, and optogenetic approaches, we show that orexin neurons, via activation of OrxR1 in the LC, facilitate the acquisition of amygdala-dependent threat memory.