Structural interactions of a voltage sensor toxin with lipid membranes

Protein toxins from tarantula venom alter the activity of diverse ion channel proteins, including voltage, stretch, and ligand-activated cation channels. Although tarantula toxins have been shown to partition into membranes, and the membrane is thought to play an important role in their activity, the structural interactions between these toxins and lipid membranes are poorly understood. Here, we use solid-state NMR and neutron diffraction to investigate the interactions between a voltage sensor toxin (VSTx1) and lipid membranes, with the goal of localizing the toxin in the membrane and determining its influence on membrane structure. Our results demonstrate that VSTx1 localizes to the headgroup region of lipid membranes and produces a thinning of the bilayer. The toxin orients such that many basic residues are in the aqueous phase, all three Trp residues adopt interfacial positions, and several hydrophobic residues are within the membrane interior. One remarkable feature of this preferred orientation is that the surface of the toxin that mediates binding to voltage sensors is ideally positioned within the lipid bilayer to favor complex formation between the toxin and the voltage sensor.Protein toxins from venomous organisms have been invaluable tools for studying the ion channel proteins they target. For example, in the case of voltage-activated potassium (Kv) channels, pore-blocking scorpion toxins were used to identify the pore-forming region of the channel (1, 2), and gating modifier tarantula toxins that bind to S1–S4 voltage-sensing domains have helped to identify structural motifs that move at the protein–lipid interface (3–5). In many instances, these toxin–channel interactions are highly specific, allowing them to be used in target validation and drug development (6–8).Tarantula toxins are a particularly interesting class of protein toxins that have been found to target all three families of voltage-activated cation channels (3, 9–12), stretch-activated cation channels (13–15), as well as ligand-gated ion channels as diverse as acid-sensing ion channels (ASIC) (16–21) and transient receptor potential (TRP) channels (22, 23). The tarantula toxins targeting these ion channels belong to the inhibitor cystine knot (ICK) family of venom toxins that are stabilized by three disulfide bonds at the core of the molecule (16, 17, 24–31). Although conventional tarantula toxins vary in length from 30 to 40 aa and contain one ICK motif, the recently discovered double-knot toxin (DkTx) that specifically targets TRPV1 channels contains two separable lobes, each containing its own ICK motif (22, 23).One unifying feature of all tarantula toxins studied thus far is that they act on ion channels by modifying the gating properties of the channel. The best studied of these are the tarantula toxins targeting voltage-activated cation channels, where the toxins bind to the S3b–S4 voltage sensor paddle motif (5, 32–36), a helix-turn-helix motif within S1–S4 voltage-sensing domains that moves in response to changes in membrane voltage (37–41). Toxins binding to S3b–S4 motifs can influence voltage sensor activation, opening and closing of the pore, or the process of inactivation (4, 5, 36, 42–46). The tarantula toxin PcTx1 can promote opening of ASIC channels at neutral pH (16, 18), and DkTx opens TRPV1 in the absence of other stimuli (22, 23), suggesting that these toxin stabilize open states of their target channels.For many of these tarantula toxins, the lipid membrane plays a key role in the mechanism of inhibition. Strong membrane partitioning has been demonstrated for a range of toxins targeting S1–S4 domains in voltage-activated channels (27, 44, 47–50), and for GsMTx4 (14, 50), a tarantula toxin that inhibits opening of stretch-activated cation channels in astrocytes, as well as the cloned stretch-activated Piezo1 channel (13, 15). In experiments on stretch-activated channels, both the d- and l-enantiomers of GsMTx4 are active (14, 50), implying that the toxin may not bind directly to the channel. In addition, both forms of the toxin alter the conductance and lifetimes of gramicidin channels (14), suggesting that the toxin inhibits stretch-activated channels by perturbing the interface between the membrane and the channel. In the case of Kv channels, the S1–S4 domains are embedded in the lipid bilayer and interact intimately with lipids (48, 51, 52) and modification in the lipid composition can dramatically alter gating of the channel (48, 53–56). In one study on the gating of the Kv2.1/Kv1.2 paddle chimera (53), the tarantula toxin VSTx1 was proposed to inhibit Kv channels by modifying the forces acting between the channel and the membrane. Although these studies implicate a key role for the membrane in the activity of Kv and stretch-activated channels, and for the action of tarantula toxins, the influence of the toxin on membrane structure and dynamics have not been directly examined. The goal of the present study was to localize a tarantula toxin in membranes using structural approaches and to investigate the influence of the toxin on the structure of the lipid bilayer.     

Quantitative analysis of vesicle recycling at the calyx of Held synapse

Vesicle recycling is pivotal for maintaining reliable synaptic signaling, but its basic properties remain poorly understood. Here, we developed an approach to quantitatively analyze the kinetics of vesicle recycling with exquisite signal and temporal resolution at the calyx of Held synapse. The combination of this electrophysiological approach with electron microscopy revealed that ∼80% of vesicles (∼270,000 out of ∼330,000) in the nerve terminal are involved in recycling. Under sustained stimulation, recycled vesicles start to be reused in tens of seconds when ∼47% of the preserved vesicles in the recycling pool (RP) are depleted. The heterogeneity of vesicle recycling as well as two kinetic components of RP depletion revealed the existence of a replenishable pool of vesicles before the priming stage and led to a realistic kinetic model that assesses the size of the subpools of the RP. Thus, our study quantified the kinetics of vesicle recycling and kinetically dissected the whole vesicle pool in the calyceal terminal into the readily releasable pool (∼0.6%), the readily priming pool (∼46%), the premature pool (∼33%), and the resting pool (∼20%).Synaptic vesicle recycling ensures synaptic transmission during sustained neuronal activity (1–3). Despite its crucial role, the cycle is poorly understood. In contrast to vesicle exocytosis and endocytosis, which can be directly assayed by presynaptic capacitance measurements and postsynaptic current recordings, vesicle recycling is usually investigated by fluorescence imaging and electron microscopy (EM) with limited signal or temporal resolution (4–7). Likely owing to technical difficulties, the basic properties of vesicle recycling, such as the size of the recycling pool (RP) (3, 6, 8–11), the kinetics of vesicle recycling (6, 8–12), and how the RP supports synaptic transmission (1, 13–15) remain to be elucidated. Classically, presynaptic vesicles can be functionally divided into three populations: the readily releasable pool (RRP), the reserve pool, and the resting pool (3, 16, 17). The RRP is defined as being composed of docked and immediately releasable vesicles (17), which are usually depleted by high-frequency stimulation, prolonged presynaptic depolarization, or the application of hypertonic solution (18–21). The reserve pool functions as a reservoir and serves to maintain vesicle refilling into the RRP (2, 3). These two pools together are commonly referred to as the RP. The resting pool serves as a depot of vesicles for backup use (16, 22). However, it has been debated for a decade whether nerve terminals use the majority (∼100%, from electrophysiology) or only a small fraction (5–40%, from fluorescence imaging and EM) of vesicles in recycling, and whether the RP size undergoes dynamic changes during varied neuronal activity (6, 7, 23–28).The use of vesicles in recycling is a critical determinant of synaptic transmission (1, 13–15). However, it has never been rigorously determined how fast recently recaptured vesicles are organized to recycle and whether vesicles in the RP are homogeneously ready for use (25). Two forms of vesicle retrieval, “kiss-and-run” and full collapse, have been reported for many years. It is still ambiguous whether the rapidly recaptured vesicles in the kiss-and-run mode can be rapidly reused (29–31).Here, we addressed the above issues by developing a new approach to quantify the basic properties of vesicle recycling with unparalleled precision. Different from previous studies in cultured cell systems, the present work combined electrophysiological measurements and EM observations at the calyx of Held synapse in acute brain slices, quantitatively analyzed synaptic vesicle recycling, and kinetically dissected the recycling vesicle pool. We propose a realistic kinetic model and provide new insights into the mechanism that ensures rate-limited but sustainable synaptic transmission.     

Dopamine release from transplanted neural stem cells in Parkinsonian rat striatum in vivo

Embryonic stem cell-based therapies exhibit great potential for the treatment of Parkinson’s disease (PD) because they can significantly rescue PD-like behaviors. However, whether the transplanted cells themselves release dopamine in vivo remains elusive. We and others have recently induced human embryonic stem cells into primitive neural stem cells (pNSCs) that are self-renewable for massive/transplantable production and can efficiently differentiate into dopamine-like neurons (pNSC–DAn) in culture. Here, we showed that after the striatal transplantation of pNSC–DAn, (i) pNSC–DAn retained tyrosine hydroxylase expression and reduced PD-like asymmetric rotation; (ii) depolarization-evoked dopamine release and reuptake were significantly rescued in the striatum both in vitro (brain slices) and in vivo, as determined jointly by microdialysis-based HPLC and electrochemical carbon fiber electrodes; and (iii) the rescued dopamine was released directly from the grafted pNSC–DAn (and not from injured original cells). Thus, pNSC–DAn grafts release and reuptake dopamine in the striatum in vivo and alleviate PD symptoms in rats, providing proof-of-concept for human clinical translation.Parkinson’s disease (PD) is a chronic progressive neurodegenerative disorder characterized by the specific loss of dopaminergic neurons in the substantia nigra pars compacta and their projecting axons, resulting in loss of dopamine (DA) release in the striatum (1). During the last two decades, cell-replacement therapy has proven, at least experimentally, to be a potential treatment for PD patients (2–7) and in animal models (8–15). The basic principle of cell therapy is to restore the DA release by transplanting new DA-like cells. Until recently, obtaining enough transplantable cells was a major bottleneck in the practicability of cell therapy for PD. One possible source is embryonic stem cells (ESCs), which can develop infinitely into self-renewable pluripotent cells with the potential to generate any type of cell, including DA neurons (DAns) (16, 17).Recently, several groups including us have introduced rapid and efficient ways to generate primitive neural stem cells (pNSCs) from human ESCs using small-molecule inhibitors under chemically defined conditions (12, 18, 19). These cells are nonpolarized neuroepithelia and retain plasticity upon treatment with neuronal developmental morphogens. Importantly, pNSCs differentiate into DAns (pNSC–DAn) with high efficiency (∼65%) after patterning by sonic hedgehog (SHH) and fibroblast growth factor 8 (FGF8) in vitro, providing an immediate and renewable source of DAns for PD treatment. Importantly, the striatal transplantation of human ESC-derived DA-like neurons, including pNSC–DAn, are able to relieve the motor defects in a PD rat model (11–13, 15, 19–23). Before attempting clinical translation of pNSC–DAn, however, there are two fundamental open questions. (i) Can pNSC–DAn functionally restore the striatal DA levels in vivo? (ii) What cells release the restored DA, pNSC–DAn themselves or resident neurons/cells repaired by the transplants?Regarding question 1, a recent study using nafion-coated carbon fiber electrodes (CFEs) reported that the amperometric current is rescued in vivo by ESC (pNSC–DAn-like) therapy (19). Both norepinephrine (NE) and serotonin are present in the striatum (24, 25). However, CFE amperometry/chronoamperometry alone cannot distinguish DA from other monoamines in vivo, such as NE and serotonin (Fig. S1) (see also refs. 26–28). Considering that the compounds released from grafted ESC-derived cells are unknown, the work of Kirkeby et al. was unable to determine whether DA or other monoamines are responsible for the restored amperometric signal. Thus, the key question of whether pNSC–DAn can rescue DA release needs to be reexamined for the identity of the restored amperometric signal in vivo.Regarding question 2, many studies have proposed that DA is probably released from the grafted cells (8, 12, 13, 20), whereas others have proposed that the grafted stem cells might restore striatal DA levels by rescuing injured original cells (29, 30). Thus, whether the grafted cells are actually capable of synthesizing and releasing DA in vivo must be investigated to determine the future cellular targets (residual cells versus pNSC–DAn) of treatment.To address these two mechanistic questions, advanced in vivo methods of DA identification and DA recording at high spatiotemporal resolution are required. Currently, microdialysis-based HPLC (HPLC) (31–33) and CFE amperometric recordings (34, 35) have been used independently by different laboratories to assess evoked DA release from the striatum in vivo. The major advantage of microdialysis-based HPLC is to identify the substances secreted in the cell-grafted striatum (33), but its spatiotemporal resolution is too low to distinguish the DA release site (residual cells or pNSC–DAn). In contrast, the major advantage of CFE-based amperometry is its very high temporal (ms) and spatial (μm) resolution, making it possible to distinguish the DA release site (residual cells or pNSC–DAn) in cultured cells, brain slices, and in vivo (34–39), but it is unable to distinguish between low-level endogenous oxidizable substances (DA versus serotonin and NE) in vivo.In the present study, we developed a challenging experimental paradigm of combining the two in vivo methods, microdialysis-based HPLC and CFE amperometry, to identify the evoked substance as DA and its release site as pNSC–DAn in the striatum of PD rats.     

Kinetics of nucleotide-dependent structural transitions in the kinesin-1 hydrolysis cycle

To dissect the kinetics of structural transitions underlying the stepping cycle of kinesin-1 at physiological ATP, we used interferometric scattering microscopy to track the position of gold nanoparticles attached to individual motor domains in processively stepping dimers. Labeled heads resided stably at positions 16.4 nm apart, corresponding to a microtubule-bound state, and at a previously unseen intermediate position, corresponding to a tethered state. The chemical transitions underlying these structural transitions were identified by varying nucleotide conditions and carrying out parallel stopped-flow kinetics assays. At saturating ATP, kinesin-1 spends half of each stepping cycle with one head bound, specifying a structural state for each of two rate-limiting transitions. Analysis of stepping kinetics in varying nucleotides shows that ATP binding is required to properly enter the one-head–bound state, and hydrolysis is necessary to exit it at a physiological rate. These transitions differ from the standard model in which ATP binding drives full docking of the flexible neck linker domain of the motor. Thus, this work defines a consensus sequence of mechanochemical transitions that can be used to understand functional diversity across the kinesin superfamily.Kinesin-1 is a motor protein that steps processively toward microtubule plus-ends, tracking single protofilaments and hydrolyzing one ATP molecule per step (1–6). Step sizes corresponding to the tubulin dimer spacing of 8.2 nm are observed when the molecule is labeled by its C-terminal tail (7–10) and to a two-dimer spacing of 16.4 nm when a single motor domain is labeled (4, 11, 12), consistent with the motor walking in a hand-over-hand fashion. Kinesin has served as an important model system for advancing single-molecule techniques (7–10) and is clinically relevant for its role in neurodegenerative diseases (13), making dissection of its step a popular ongoing target of study.Despite decades of work, many essential components of the mechanochemical cycle remain disputed, including (i) how much time kinesin-1 spends in a one-head–bound (1HB) state when stepping at physiological ATP concentrations, (ii) whether the motor waits for ATP in a 1HB or two-heads–bound (2HB) state, and (iii) whether ATP hydrolysis occurs before or after tethered head attachment (4, 11, 14–20). These questions are important because they are fundamental to the mechanism by which kinesins harness nucleotide-dependent structural changes to generate mechanical force in a manner optimized for their specific cellular tasks. Addressing these questions requires characterizing a transient 1HB state in the stepping cycle in which the unattached head is located between successive binding sites on the microtubule. This 1HB intermediate is associated with the force-generating powerstroke of the motor and underlies the detachment pathway that limits motor processivity. Optical trapping (7, 19, 21, 22) and single-molecule tracking studies (4, 8–11) have failed to detect this 1HB state during stepping. Single-molecule fluorescence approaches have detected a 1HB intermediate at limiting ATP concentrations (11, 12, 14, 15), but apart from one study that used autocorrelation analysis to detect a 3-ms intermediate (17), the 1HB state has been undetectable at physiological ATP concentrations.Single-molecule microscopy is a powerful tool for studying the kinetics of structural changes in macromolecules (23). Tracking steps and potential substeps for kinesin-1 at saturating ATP has until now been hampered by the high stepping rates of the motor (up to 100 s⁻¹), which necessitates high frame rates, and the small step size (8.2 nm), which necessitates high spatial precision (7). Here, we apply interferometric scattering microscopy (iSCAT), a recently established single-molecule tool with high spatiotemporal resolution (24–27) to directly visualize the structural changes underlying kinesin stepping. By labeling one motor domain in a dimeric motor, we detect a 1HB intermediate state in which the tethered head resides over the bound head for half the duration of the stepping cycle at saturating ATP. We further show that at physiological stepping rates, ATP binding is required to enter this 1HB state and that ATP hydrolysis is required to exit it. This work leads to a significant revision of the sequence and kinetics of mechanochemical transitions that make up the kinesin-1 stepping cycle and provides a framework for understanding functional diversity across the kinesin superfamily.     

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.     

Structural insights into the interaction of IL-33 with its receptors

Interleukin (IL)-33 is an important member of the IL-1 family that has pleiotropic activities in innate and adaptive immune responses in host defense and disease. It signals through its ligand-binding primary receptor ST2 and IL-1 receptor accessory protein (IL-1RAcP), both of which are members of the IL-1 receptor family. To clarify the interaction of IL-33 with its receptors, we determined the crystal structure of IL-33 in complex with the ectodomain of ST2 at a resolution of 3.27 Å. Coupled with structure-based mutagenesis and binding assay, the structural results define the molecular mechanism by which ST2 specifically recognizes IL-33. Structural comparison with other ligand–receptor complexes in the IL-1 family indicates that surface-charge complementarity is critical in determining ligand-binding specificity of IL-1 primary receptors. Combined crystallography and small-angle X-ray–scattering studies reveal that ST2 possesses hinge flexibility between the D3 domain and D1D2 module, whereas IL-1RAcP exhibits a rigid conformation in the unbound state in solution. The molecular flexibility of ST2 provides structural insights into domain-level conformational change of IL-1 primary receptors upon ligand binding, and the rigidity of IL-1RAcP explains its inability to bind ligands directly. The solution architecture of IL-33–ST2–IL-1RAcP complex from small-angle X-ray–scattering analysis resembles IL-1β–IL-1RII–IL-1RAcP and IL-1β–IL-1RI–IL-1RAcP crystal structures. The collective results confer IL-33 structure–function relationships, supporting and extending a general model for ligand–receptor assembly and activation in the IL-1 family.Interleukin (IL)-33 has important roles in initiating a type 2 immune response during infectious, inflammatory, and allergic diseases (1–5). It was initially identified as a nuclear factor in endothelial cells and named NF-HEV (nuclear factor from high endothelial venules) (6, 7). In 2005, it was rediscovered as a new member of the IL-1 family and an extracellular ligand for the orphan IL-1 receptor family member ST2 (8). As an extracellular cytokine, IL-33 is involved in the polarization of Th2 cells and activation of mast cells, basophils, eosinophils, and natural killer cells (1–3). Recent studies also discovered that the type 2 innate lymphoid cells (ILC2s) are major target cells of IL-33 (9, 10). ILC2s express a high level of ST2 and secrete large amounts of Th2 cytokines, most notably IL-5 and IL-13, when stimulated with IL-33 (11–13). Activation of ILC2s is essential in the initiation of the type 2 immune response against helminth infection and during allergic diseases such as asthma (9, 10).IL-33 does not have a signal peptide and is synthesized with an N-terminal propeptide upstream of the IL-1–like cytokine domain. It is preferentially and constitutively expressed in the nuclei of structural and lining cells, particularly in epithelial and endothelial cells (14, 15). Tissue damage caused by pathogen invasion or allergen exposure may lead to the release of IL-33 into extracellular environment from necrotic cells, which functions as an endogenous danger signal or alarmin (14, 16). Full-length human IL-33 consists of 270 residues and is biologically active (17, 18). It is also a substrate of serine proteases released by inflammatory cells recruited to the site of injury (18, 19). The proteases elastase, cathespin G, and proteinase 3 cleave full-length IL-33 to release N-terminal–truncated mature forms containing the IL-1–like cytokine domain: IL-33_95–270, l-33_99–270, and IL-33_109–270 (18). These mature IL-33 forms process a 10-fold greater potency to activate ST2 than full-length IL-33 (18). Caspase-1 was also suggested to cleave IL-33 to generate an active IL-33_112–270 that is the commercially available mature IL-33 form (8). However, it was later demonstrated that this cleavage site does not exist and cleavage by caspases at other sites actually inactivates IL-33 (17, 20, 21).The signaling of IL-33 depends on its binding to the primary receptor ST2 and subsequent recruitment of accessory receptor IL-1RAcP (8, 22, 23). The ligand-binding–induced receptor heterodimerization results in the juxtaposition of the intracellular toll/interleukin-1 receptor (TIR) domains of both receptors, which is necessary and sufficient to activate NF-κB and MAPK pathways in the target cells (24). Previously, we determined the complex structure of IL-1β with its decoy receptor IL-1RII and accessory receptor IL-1RAcP (25). Based on this structure and other previous studies, we proposed a general structural model for the assembly and activation of IL-1 family of cytokines with their receptors (25). In this model, ligand recognition relies on interaction of IL-1 cytokine with its primary receptor: IL-1α and IL-1β with IL-1RI; IL-33 with ST2; IL-18 with IL-18Rα; and IL-36α, IL-36β, and IL-36γ with IL-1Rrp2 (26–28). The binding forms a composite surface to recruit accessory receptor IL-1RAcP shared by IL-1α, IL-1β, IL-33, IL-36α, IL-36β, and IL-36γ and IL-18Rβ by IL-18 (26, 27). This general structural model is further supported by the subsequent structural determination of IL-1β with IL-1RI and IL-1RAcP (29). However, there are still many key missing parts in the general structural model of ligand–receptor interaction in the IL-1 family. For example, the structural basis for specific recognition of IL-33 by ST2 and IL-18 by IL-18Rα, and promiscuous recognition of IL-36α, IL-36β, and IL-36γ by IL-1Rrp2 remains elusive. The proposed general model also needs further confirmation from structural studies of other signaling complexes in the IL-1 family. To address these issues, we studied the interaction of IL-33 with its receptors by a combination of X-ray crystallography and small-angle X-ray–scattering (SAXS) methods.     

Microscopic identification of the order parameter governing liquid–liquid transition in a molecular liquid

A liquid–liquid transition (LLT) in a single-component substance is an unconventional phase transition from one liquid to another. LLT has recently attracted considerable attention because of its fundamental importance in our understanding of the liquid state. To access the order parameter governing LLT from a microscopic viewpoint, here we follow the structural evolution during the LLT of an organic molecular liquid, triphenyl phosphite (TPP), by time-resolved small- and wide-angle X-ray scattering measurements. We find that locally favored clusters, whose characteristic size is a few nanometers, are spontaneously formed and their number density monotonically increases during LLT. This strongly suggests that the order parameter of LLT is the number density of locally favored structures and of nonconserved nature. We also show that the locally favored structures are distinct from the crystal structure and these two types of orderings compete with each other. Thus, our study not only experimentally identifies the structural order parameter governing LLT, but also may settle a long-standing debate on the nature of the transition in TPP, i.e., whether the transition is LLT or merely microcrystal formation.Liquid-liquid transition (LLT) is an intriguing phenomenon in which a liquid transforms into another one via a first-order transition. This means that there can be more than two liquid states for a single-component substance. Despite its counterintuitive nature, there have recently been many pieces of experimental and numerical evidence for the existence of LLT, for various liquids such as water (1–5), aqueous solutions (6–8), triphenyl phosphite (9–12), l-butanol (13), phosphorus (14), silicon (15, 16), germanium (17), and Y₂O₃–Al₂O₃ (18, 19). This suggests that the LLT may be rather universally observed for various types of liquids. However, none of the LLTs reported so far is free from criticisms (20, 21), mainly because these LLTs take place under experimentally difficult conditions [e.g., at high temperature and pressure (14, 15, 17–19)] or in a supercooled state below the melting point (1–3, 5–7, 9, 10), where the transition is inevitably contaminated by microcrystal formation. The latter is not limited to experiments but arises in numerical simulations, often causing many controversies [LLT (22–25) vs. crystallization (26–28)]. For ST2 water, however, this issue has recently been settled by an extensive simulation study by Palmer et al. (4).One of the hottest and long-standing debates is on the nature of the transition found in a molecular liquid, triphenyl phosphite (TPP), by Kivelson and his coworkers (29). The transition is very easy to access experimentally, because it takes place at ambient pressure and at a temperature range between 230 and 210 K and the transformation speed is slow enough to follow the kinetics. Since the finding of this transition (29, 30), many researchers thus have been interested in this intriguing phenomenon and there have been hot discussions on the nature of the transition (20, 21). Some people interpreted this as a liquid-associated phenomenon (9, 10, 31, 32), but others interpret it differently. All of the controversies come from the fact that this transition accompanies microcrystal formation and thus the final state, which is called “glacial phase,” often contains microcrystallites. This led many researchers to explain the transition by non-LLT scenarios, which include a defect-ordered phase scenario predicted by a frustration limited domain theory (29, 30, 33, 34), a microcrystallization scenario (35–38), and a liquid-crystal or plastic-crystal phase scenario (39). Each scenario captures a certain feature of the glacial phase, but fails in explaining all of the experimental results in a consistent manner. Similar situations are often seen in other candidates of LLTs, such as l-butanol [LLT (13) vs. microcrystallization (40–43)], confined water [LLT (5) vs. other phenomena (44–46)], and aqueous solutions [LLT (6, 7) vs. microcrystallization (8, 28, 47, 48)]. For TPP, however, some pieces of experimental evidence supportive of the LLT scenario rather than the microcrystallization scenario have recently been reported (11, 12).We propose a two-order-parameter (TOP) model of a liquid to explain LLT (20, 49). The main point of this model is that it is necessary to consider the spatiotemporal hierarchical nature of a liquid to understand LLT. More specifically, we argue that in addition to density order parameter ρ describing a gas–liquid transition, we need an additional scalar order parameter S, which is the number density of locally favored structures (LFS). In this model, LLT is a consequence of the cooperative ordering of the scalar nonconserved order parameter S, i.e., the cooperative formation of LFS. In other words, LLT is regarded as a gas–liquid-like transition of LFS: one liquid is a gas state of LFS (low-S state), and the other is its liquid state (high-S state). Recently, it was proposed by Anisimov and coworkers (50, 51) that the thermodynamic ordering field conjugate to the order parameter is the conversion equilibrium constant, which further characterizes the nature of LLT. We explained our experimental observation of LLT in TPP in terms of this model (9, 10). We also studied the phase transition dynamics and the physical and chemical properties of the second liquid state (liquid II), which were also explained by the model (20, 21).However, we have not had any direct experimental evidence for the formation of such LFS up to now; thus, an open question is, what is the relevant order parameter governing LLT, although the link of the order parameter to the enthalpy (9, 10), the refractive index (or, density) (9, 10, 29, 30), and the polarity associated with local molecular ordering (12) has been suggested for LLT in TPP. There have been structural studies on LLT by X-ray and neutron scattering measurements, focusing on local liquid structures at an inter- and intramolecular scale (36, 38, 52–54) and mesoscopic structures (34, 55). However, there has been no experimental evidence for the presence of locally favored structures, which characterize the liquid state uniquely, or the order parameter has still not been identified from a microscopic viewpoint.Here we study the structural change of TPP during LLT by time-resolved small- and wide-angle X-ray scattering measurements, which cover a length scale from a single molecule size ( ～  1 nm) to more than tens of nanometers. We show, to our knowledge, the first direct evidence for the presence of LFS and the temporal increase upon the liquid I-to-liquid II transformation. Furthermore, we also find an indication of the formation of microcrystallites during LLT. However, we reveal that LFS and microcrystallites have different sizes and growth kinetics, indicating that although they sometimes appear simultaneously during the process of LLT, LLT itself is driven by the formation of LFS and not by that of microcrystallites. We also discover that LFS are destroyed upon crystallization, clearly indicating not only that these two types of orderings are competing with each other but also that LFS is a structure unique to the liquid state. Our findings provide a comprehensive view on the long-standing controversy on the origin of the glacial phase, which was discovered by Kivelson and his coworkers (29, 30), and show that the fraction of LFS may be the relevant order parameter of LLT. This suggests that a liquid can have a spatiotemporal hierarchical structure at a low temperature, contrary to the common picture of a high-temperature liquid where the structure is random and homogeneous beyond the molecular size.     

Therapeutic mechanisms of high-frequency stimulation in Parkinson’s disease and neural restoration via loop-based reinforcement

High-frequency deep brain stimulation (HFS) is clinically recognized to treat parkinsonian movement disorders, but its mechanisms remain elusive. Current hypotheses suggest that the therapeutic merit of HFS stems from increasing the regularity of the firing patterns in the basal ganglia (BG). Although this is consistent with experiments in humans and animal models of Parkinsonism, it is unclear how the pattern regularization would originate from HFS. To address this question, we built a computational model of the cortico-BG-thalamo-cortical loop in normal and parkinsonian conditions. We simulated the effects of subthalamic deep brain stimulation both proximally to the stimulation site and distally through orthodromic and antidromic mechanisms for several stimulation frequencies (20–180 Hz) and, correspondingly, we studied the evolution of the firing patterns in the loop. The model closely reproduced experimental evidence for each structure in the loop and showed that neither the proximal effects nor the distal effects individually account for the observed pattern changes, whereas the combined impact of these effects increases with the stimulation frequency and becomes significant for HFS. Perturbations evoked proximally and distally propagate along the loop, rendezvous in the striatum, and, for HFS, positively overlap (reinforcement), thus causing larger poststimulus activation and more regular patterns in striatum. Reinforcement is maximal for the clinically relevant 130-Hz stimulation and restores a more normal activity in the nuclei downstream. These results suggest that reinforcement may be pivotal to achieve pattern regularization and restore the neural activity in the nuclei downstream and may stem from frequency-selective resonant properties of the loop.High-frequency (i.e., above 100 Hz) deep brain stimulation (HFS) of the basal ganglia (BG) and thalamus is clinically recognized to treat movement disorders in Parkinson’s disease (PD) (1–4), but its therapeutic mechanisms remain unclear (5, 6).Early hypotheses about HFS were derived from the rate-based model of the BG function (7, 8) and postulated the disruption of the output of the BG-thalamic system via either the inactivation of neurons in the stimulated site (target) (9–15), which would provide an effect similar to a surgical lesion, or the abnormal excitation of axons projecting out of the target (16–19), which would disrupt the neuronal activity in the structures downstream, including any pathophysiological activity (20).More recently, an ever-growing number of experiments in PD humans and animal models of Parkinsonism has indicated that HFS affects the firing patterns of the neurons rather than the mean firing rate both in the target and the structures downstream (18, 19, 21–31) and it replaces repetitive low-frequency (i.e., ≤50 Hz) bursting patterns with regularized (i.e., more tonic) patterns at higher frequencies (25, 26). It has been proposed that increased pattern regularity of neurons in the target may be therapeutic (5, 32–37), but it is still unknown how this regularity comes about with HFS.It has been suggested that an increased pattern regularity can deplete the information content of the target output and this lack of information would act as an “information lesion” (33) and prevent the pathological activity from being transmitted within the BG-thalamic system (22, 33, 36). As a result, an information lesion in the target [typically, one among the subthalamic nucleus (STN), internal globus pallidus (GPi), or thalamus] would have effects similar to those of a destructive lesion in the same site, which has been reported to alleviate the movement disorders (38).Instead, studies (32, 34, 35, 37) have suggested that an increased pattern regularity of the BG output partly compensates the PD-evoked impairment of the information-processing capabilities of the thalamo-cortical system, and this restores a more faithful thalamic relay of the sensorimotor information (35, 39).Although intriguing, these hypotheses remain elusive on (i) the neuronal mechanisms that would elicit pattern regularization (e.g., why regularization would be relevant only for HFS) and (ii) the effects that increased regularity would have on the cortico-BG-thalamo-cortical loop.It has been hypothesized that pattern regularization occurs because axons projecting out of the target follow the pattern of the stimulus pulses (40, 41) and, given the segregated organization of the BG-thalamic connections (42), it has been assumed that pattern regularization percolates straightforward from the target to the structures immediately downstream (34, 36). However, this representation of the pattern regularization as a “local” effect can hardly be reconciled with the fact that HFS of any structure of the cortico-BG-thalamo-cortical loop is therapeutic for at least some movement disorders (1–4, 43–47), nor does it explain why stimulation at frequencies above 160–180 Hz is not necessarily therapeutic despite the fact that the regularity of the axonal patterns may increase (48, 49). Moreover, coherence in the 8–30-Hz band among neurons across different structures may decrease under HFS but not for lower frequencies (26, 50–52), which suggests the emergence of diffused changes in neuronal activity that would be hardly accounted for with purely local effects.There is emerging evidence, instead, that HFS affects multiple structures simultaneously. First, it has been shown that deep brain stimulation (DBS) may antidromically activate afferent axons and fibers of passage (53–59), thus reaching structures not immediately downstream. Second, studies (57, 58) observed in 6-hydroxydopamine (6-OHDA)-intoxicated rats that the antidromic effects increase with the stimulation frequency and peak around 110–130 Hz. Third, it has been shown in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-intoxicated nonhuman primates (NHPs) that STN DBS may evoke similar poststimulus responses in different BG structures, both downstream from and upstream to the STN (5, 27, 28, 30, 60). Finally, it has been reported that the cortico-BG-thalamo-cortical system consists of multiple sets of reentrant, interconnected, and partially overlapping neuronal loops (5, 42, 61, 62), which means that the structures upstream to the target (e.g., the striatum) may play an important role in the therapeutic mechanisms of HFS.Altogether, these results suggest that (A) pattern regularization is a global effect that exploits the closed-loop nature of the cortico-BG-thalamo-cortical system and selectively emerges only for specific HFS values, and that (B) the therapeutic merit of pattern regularization has to deal with the restoration of a more normal functionality of the entire cortico-BG-thalamo-cortical loop rather than with variations in the information content of one specific structure.We explored hypotheses (A) and (B) and assessed the system-wide effects of DBS by constructing a computational model of the cortico-BG-thalamo-cortical loop in both normal and parkinsonian conditions and by simulating the effects of STN DBS both at low (20–80 Hz) and high (100–180 Hz) frequencies. The model includes populations of single-compartment neurons and interneurons from motor cortex, striatum, GPi, and thalamus according to a network topology derived from the NHP anatomy, and it simulates both the orthodromic and antidromic effects of DBS. As a result, this model reproduced both average activity and discharge patterns of single units in NHP and rats under normal and parkinsonian conditions, with and without DBS, for all modeled structures.We show through numerical simulation that hypothesis (A) is significantly contributed by reinforcement mechanisms in the striatum. These mechanisms are selectively elicited by HFS, facilitate the percolation of regularized discharge patterns from the striatum to the GPi, and have a primary role in (B), because the percolated striato-pallidal input combines with the local effects of STN DBS to restore the thalamic relay function (63).     

Predictive Value of Brain Natriuretic Peptides in Patients on Peritoneal Dialysis: Results from the ADEMEX Trial

Background and objectives: Natriuretic peptides have been suggested to be of value in risk stratification in dialysis patients. Data in patients on peritoneal dialysis remain limited.Design, setting, participants, & measurements: Patients of the ADEMEX trial (ADEquacy of peritoneal dialysis in MEXico) were randomized to a control group [standard 4 × 2L continuous ambulatory peritoneal dialysis (CAPD); n = 484] and an intervention group (CAPD with a target creatinine clearance ≥60L/wk/1.73 m²; n = 481). Natriuretic peptides were measured at baseline and correlated with other parameters as well as evaluated for effects on patient outcomes.Results: Control group and intervention group were comparable at baseline with respect to all measured parameters. Baseline values of natriuretic peptides were elevated and correlated significantly with levels of residual renal function but not with body size or diabetes. Baseline values of N-terminal fragment of B-type natriuretic peptide (NT-proBNP) but not proANP(1–30), proANP(31–67), or proANP(1–98) were independently highly predictive of overall survival and cardiovascular mortality. Volume removal was also significantly correlated with patient survival.Conclusions. NT-proBNP have a significant predictive value for survival of CAPD patients and may be of value in guiding risk stratification and potentially targeted therapeutic interventions.Plasma levels of cardiac natriuretic peptides are elevated in patients with chronic kidney disease, owing to impairment of renal function, hypertension, hypervolemia, and/or concomitant heart disease (1–7). Atrial natriuretic peptide (ANP) and particularly brain natriuretic peptide (BNP) levels are linked independently to left ventricular mass (3–5,8–16) and function (3,6–17) and predict total and cardiovascular mortality (1,3,8,10,12,18) as well as cardiac events (12,19). ANP and BNP decrease significantly during hemodialysis treatment but increase again during the interdialytic interval (1,2,4,6,7,14,17,20–23). Levels in patients on peritoneal dialysis (PD) have been found to be lower than in patients on hemodialysis (11,24–26), but the correlations with left ventricular function and structure are maintained in both types of dialysis modalities (11,15,27,28).The high mortality of patients on peritoneal dialysis and the failure of dialytic interventions to alter this mortality (29,30) necessitate renewed attention into novel methods of stratification and identification of patients at highest risk to be targeted for specific interventions. Cardiac natriuretic peptides are increasingly considered to fulfill this role in nonrenal patients. Evaluations of cardiac natriuretic peptides in patients on PD have been limited by small numbers (3,9,11,12,15,24–26) and only one study examined correlations between natriuretic peptide levels and outcomes (12). The PD population enrolled in the ADEMEX trial offered us the opportunity to evaluate cardiac natriuretic peptides and their value in predicting outcomes in the largest clinical trial ever performed on PD (29,30). It is hoped that such an evaluation would identify patients at risk even in the absence of overt clinical disease and hence facilitate or encourage interventions with salutary outcomes.     

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.     

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.     

Effects of lymphocyte profile on development of EBV-induced lymphoma subtypes in humanized mice

Epstein-Barr virus (EBV) infection causes both Hodgkin’s lymphoma (HL) and non-Hodgkin’s lymphoma (NHL). The present study reveals that EBV-induced HL and NHL are intriguingly associated with a repopulated immune cell profile in humanized mice. Newborn immunodeficient NSG mice were engrafted with human cord blood CD34⁺ hematopoietic stem cells (HSCs) for a 8- or 15-wk reconstitution period (denoted ^8whN and ^15whN, respectively), resulting in human B-cell and T-cell predominance in peripheral blood cells, respectively. Further, novel humanized mice were established via engraftment of hCD34⁺ HSCs together with nonautologous fetal liver-derived mesenchymal stem cells (MSCs) or MSCs expressing an active notch ligand DLK1, resulting in mice skewed with human B or T cells, respectively. After EBV infection, whereas NHL developed more frequently in B-cell–predominant humanized mice, HL was seen in T-cell–predominant mice (P = 0.0013). Whereas human splenocytes from NHL-bearing mice were positive for EBV-associated NHL markers (hBCL2⁺, hCD20⁺, hKi67⁺, hCD20⁺/EBNA1⁺, and EBER⁺) but negative for HL markers (LMP1⁻, EBNA2⁻, and hCD30⁻), most HL-like tumors were characterized by the presence of malignant Hodgkin’s Reed–Sternberg (HRS)-like cells, lacunar RS (hCD30⁺, hCD15⁺, IgJ⁻, EBER⁺/hCD30⁺, EBNA1⁺/hCD30⁺, LMP⁺/EBNA2⁻, hCD68⁺, hBCL2⁻, hCD20^-/weak, Phospho STAT6⁺), and mummified RS cells. This study reveals that immune cell composition plays an important role in the development of EBV-induced B-cell lymphoma.Epstein Barr virus (EBV) infects human B lymphocytes and epithelial cells in >90% of the human population (1, 2). EBV infection is widely associated with the development of diverse human disorders that include Hodgkin’s lymphoma (HL) and non-Hodgkin’s lymphomas (NHL), including diffused large B-cell lymphoma (DLBCL), follicular B-cell lymphoma (FBCL), endemic Burkitt’s lymphoma (BL), and hemophagocytic lymphohistiocytosis (HLH) (3).HL is a malignant lymphoid neoplasm most prevalent in adolescents and young adults (4–6). Hodgkin/Reed–Sternberg (HRS) cells are the sole malignant cells of HL. HRS cells are characterized by CD30⁺/CD15⁺/BCL6⁻/CD20^+/− markers and appear large and multinucleated owing to multiple nuclear divisions without cytokinesis. Although HRS cells are malignant in the body, surrounding inflammatory cells greatly outnumber them. These reactive nonmalignant inflammatory cells, including lymphocytes, histiocytes, eosinophils, fibroblasts, neutrophils, and plasma cells, compose the vast majority of the tumor mass. The presence of HRS cells in the context of this inflammatory cellular background is a critical hallmark of the HL diagnosis (4). Approximately 50% of HL cases are EBV-associated (EBVaHL) (7–11). EBV-positive HRS cells express EBV latent membrane protein (LMP) 1 (LMP1), LMP2A, LMP2B, and EBV nuclear antigen (EBNA) 1 (EBNA1), but lack EBNA2 (latency II marker) (12). LMP1 is consistently expressed in all EBV-associated cases of classical HL (13, 14). LMP1 mimics activated CD40 receptors, induces NF-κB, and allows cells to become malignant while escaping apoptosis (15).The etiologic role of EBV in numerous disorders has been studied in humanized mouse models in diverse experimental conditions. Humanized mouse models recapitulate key characteristics of EBV infection-associated disease pathogenesis (16–24). Different settings have given rise to quite distinct phenotypes, including B-cell type NHL (DLBCL, FBCL, and unspecified B-cell lymphomas), natural killer/T cell lymphoma (NKTCL), nonmalignant lymphoproliferative disorder (LPD), extremely rare HL, HLH, and arthritis (16–24). Despite considerable efforts (16–24), EBVaHL has not been properly produced in the humanized mouse setting model, owing to inappropriate animal models and a lack of in-depth analyses. After an initial report of infected humanized mice, HRS-like cells appeared to be extremely rare in the spleens of infected humanized mice; however, the findings were inconclusive (18). Here we report direct evidence of EBVaHL or HL-like neoplasms in multiple humanized mice in which T cells were predominant over B cells. Our study demonstrates that EBV-infected humanized mice display additional EBV-associated pathogenesis, including DLBCL and hemophagocytic lymphohistiocytosis (16, 17).     

Retinal waves regulate afferent terminal targeting in the early visual pathway

Current models of retinogeniculate development have proposed that connectivity between the retina and the dorsal lateral geniculate nucleus (dLGN) is established by gradients of axon guidance molecules, to allow initial coarse connections, and by competitive Hebbian-like processes, to drive eye-specific segregation and refine retinotopy. Here we show that when intereye competition is eliminated by monocular enucleation, blocking cholinergic stage II retinal waves disrupts the intraeye competition-mediated expansion of the retinogeniculate projection and results in the permanent disorganization of its laminae. This disruption of stage II retinal waves also causes long-term impacts on receptive field size and fine-scale retinotopy in the dLGN. Our results reveal a novel role for stage II retinal waves in regulating retinogeniculate afferent terminal targeting by way of intraeye competition, allowing for correct laminar patterning and the even allocation of synaptic territory. These findings should contribute to answering questions regarding the role of neural activity in guiding the establishment of neural circuits.The brain employs several strategies to guide the establishment of correct neural connectivity (1, 2). It has been well recognized that the high specificity of connections between the retina and the dorsal lateral geniculate nucleus (dLGN) is established through several factors. These include gradients of axon guidance molecules that guide the initial coarse targeting of afferent terminals (3–6), and spontaneous retinal activity (retinal waves) that drives competitive processes important for the refinement and segregation of afferent terminal branches (2, 7–15).Retinal waves are spontaneous propagating bursts of correlated retinal ganglion cell (RGC) activity and have been classified into three developmental stages (1, 15). Stage II retinal waves (from here on also referred to as retinal waves) are extensively studied and have been found to be critical for the development of retinofugal pathways (1, 2, 15). They are mediated by cholinergic signaling from starburst amacrine cells onto RGCs (8, 13, 16–18) and have been hypothesized to drive the Hebbian-like remodeling of RGC afferent terminals (19, 20). Retinal waves play crucial roles in both the establishment of eye-specific segregation (8, 12, 14, 20, 21), through the removal of afferent branches from opposing putative eye-specific domains, and the refinement of afferent terminals within eye-specific laminae, which is believed to be necessary for the establishment of fine-scale retinotopy (12, 22). However, studies have suggested that retinal waves might play additional roles in the development of the retinogeniculate pathway. When retinal waves are blocked during early development, mature lamination in the adult is abnormal (23–25), while eye-specific segregation recovers (26, 27). These results uncovered a retinal wave-dependent window for the development of retinogeniculate lamination. However, the question remains open as to whether these lamination defects are due to abnormal late eye-specific segregation or the disruption of some form of retinal wave-dependent afferent terminal targeting.A potential retinal wave-dependent mechanism that could regulate retinogeniculate afferent terminal targeting is axon–axon competition originating from the same eye (i.e., intraeye competition). Classic studies in goldfish first demonstrated the principle of axon–axon competition at the optic tectum (28). These studies showed that RGC afferent terminals can undergo expansive or compressive rearrangements in their targeting in response to changes in afferent number, or retinorecipient target size, while maintaining correct retinotopy (28–32). Similarly, neonatal monocular enucleation in ferrets results in an expanded ipsilateral and contralateral projection by adulthood, while correct laminar organization is maintained (7, 10). This demonstrates that retinogeniculate afferent terminals can undergo an expansive and orderly rearrangement due to intraeye competition, and that intereye competition is not required for the establishment of proper retinogeniculate lamination.To investigate whether retinal waves play a role in regulating retinogeniculate afferent terminal targeting by way of intraeye competition, we monocularly enucleated ferrets one day after birth (P1), to eliminate intereye competition, while also pharmacologically blocking retinal waves (P1– P10) in the surviving eye with the cholinergic agonist epibatidine (EPI) (8, 13, 18). Effects on the targeting of retinogeniculate afferents terminals were assessed anatomically, to characterize impacts on retinogeniculate lamination, and functionally, to assess changes in receptive field (RF) structure and retinotopy in the dLGN. Our results demonstrate that retinal waves regulate afferent terminal targeting by way of intraeye competition during the development of the retinogeniculate pathway.     

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.     

Warning signals are under positive frequency-dependent selection in nature

Positive frequency-dependent selection (FDS) is a selection regime where the fitness of a phenotype increases with its frequency, and it is thought to underlie important adaptive strategies resting on signaling and communication. However, whether and how positive FDS truly operates in nature remains unknown, which hampers our understanding of signal diversity. Here, we test for positive FDS operating on the warning color patterns of chemically defended butterflies forming multiple coexisting mimicry assemblages in the Amazon. Using malleable prey models placed in localities showing differences in the relative frequencies of warningly colored prey, we demonstrate that the efficiency of a warning signal increases steadily with its local frequency in the natural community, up to a threshold where protection stabilizes. The shape of this relationship is consistent with the direct effect of the local abundance of each warning signal on the corresponding avoidance knowledge of the local predator community. This relationship, which differs from purifying selection acting on each mimetic pattern, indicates that predator knowledge, integrated over the entire community, is saturated only for the most common warning signals. In contrast, among the well-established warning signals present in local prey assemblages, most are incompletely known to local predators and enjoy incomplete protection. This incomplete predator knowledge should generate strong benefits to life history traits that enhance warning efficiency by increasing the effective frequency of prey visible to predators. Strategies such as gregariousness or niche convergence between comimics may therefore readily evolve through their effects on predator knowledge and warning efficiency.Frequency-dependent selection (FDS) occurs when the fitness of a phenotype depends on its frequency in the population (1). Under negative FDS, the fitness of a phenotype will decrease as its frequency increases. This supposedly common mechanism (2) maintains adaptive polymorphism and has been documented in a variety of natural systems, ranging from foraging behavior (2, 3) and pollination syndromes (4) to predator–prey (5–7) and parasite–host coevolution (8). On the other hand, positive FDS is a selection regime where the fitness of a phenotype increases with its frequency and does not readily maintain polymorphism. However, positive FDS is thought to be a mechanism central to the evolution of a large diversity of adaptive strategies. Notably, traits used in signaling and communication, where efficiency depends on local frequency, such as languages and social signals (9), flower coloration for pollinator attraction (10), and warning signals of prey unpalatability (11), should be subjected to positive FDS. However, although the principles of positive FDS may be well understood from a theoretical point of view, the extent to which it is operating in nature remains largely unknown.Warning coloration advertising prey defenses is a textbook example of a trait under positive FDS, and is thought to be responsible for the remarkable convergence among defended prey species known as Müllerian mimicry (11, 12). The theory developed by Müller (11) posits that naive predators learn to avoid warningly colored prey after a given number of attacks, conferring improved survival to individuals bearing resemblance to a locally abundant signal. The efficiency of Müllerian mimicry is well-supported by empirical evidence. Experiments in the laboratory (13, 14) and in natural contexts (15–18) have demonstrated that naive predators have the cognitive capabilities to associate conspicuous signals with toxicity, and to avoid them later. Transplant experiments with live prey or artificial prey models performed in the field have shown increased survival for prey matching the locally abundant warning signal and lower fitness for prey with exotic or novel signals, explaining the stable geographic mosaic of locally uniform warning signals observed (16, 17, 19–21).However, selection favoring mimicry in those studies takes on the pattern of purifying selection for local signals (15, 17, 20), so the role of positive FDS in the evolution of mimicry is unclear. Indeed, distinguishing the effect of positive FDS from local purifying selection is particularly challenging because the polymorphism necessary to distinguish between them is intrinsically unstable when the most common forms are favored (15–17, 20, 22). Both selection regimes lead to population monomorphism and interspecific phenotypic convergence, but they differ importantly in the role of local frequency in defining fitness optima. Purifying selection is expected to favor the highest quality warning signal independent of frequency, whereas FDS stems from the dependence of predator knowledge on the local frequency of warning signals across species in the prey community. Therefore, understanding how selection for mimicry truly operates and shapes prey communities with multiple coexisting mimicry rings requires confirming positive FDS and distinguishing the effect of frequency itself from the intrinsic qualities of the different warning signals involved.