Bidirectional homeostatic plasticity induced by interneuron cell death and transplantation in vivo

Chronic changes in excitability and activity can induce homeostatic plasticity. These perturbations may be associated with neurological disorders, particularly those involving loss or dysfunction of GABA interneurons. In distal-less homeobox 1 (Dlx1^−/−) mice with late-onset interneuron loss and reduced inhibition, we observed both excitatory synaptic silencing and decreased intrinsic neuronal excitability. These homeostatic changes do not fully restore normal circuit function, because synaptic silencing results in enhanced potential for long-term potentiation and abnormal gamma oscillations. Transplanting medial ganglionic eminence interneuron progenitors to introduce new GABAergic interneurons, we demonstrate restoration of hippocampal function. Specifically, miniature excitatory postsynaptic currents, input resistance, hippocampal long-term potentiation, and gamma oscillations are all normalized. Thus, in vivo homeostatic plasticity is a highly dynamic and bidirectional process that responds to changes in inhibition.Prolonged changes in activity levels induce bidirectional changes in neuronal excitability and synaptic activity known as homeostatic plasticity (1, 2). This phenomenon has been described well at excitatory synapses and functions to maintain activity within a preferred dynamic range. Maintaining excitatory/inhibitory synaptic balance is critical for neuronal information processing and a potential problem when confronted with aberrant states of excitability, such as those associated with autism, schizophrenia, Alzheimer’s disease, or epilepsy (3–12).Chronic manipulation of synaptic input and/or action potential (AP) output rates in cortical and hippocampal cell cultures induces homeostatic synaptic scaling, in which the amplitude and then the frequency of pyramidal neuron miniature excitatory postsynaptic currents (mEPSCs) increase when activity is lowered or decrease when activity is raised (13–16). Recent studies have begun to reveal the underlying molecular mechanisms of homeostatic synaptic changes, including the AMPA receptor subunits, synapse-associated calcium-binding proteins, and intracellular signaling cascades involved (14, 17, 18). Changes to activity also trigger homeostatic plasticity of inhibitory synaptic transmission (19–23). Homozygous deletion of glutamate decarboxylase 1 (Gad1), the rate-limiting enzyme in the synthesis of GABA, reduced miniature inhibitory postsynaptic current (mIPSC) amplitudes in cultured hippocampal neurons but also blocked further homeostatic changes to mIPSCs. This suggests a key role for regulation of Gad1 expression in inhibitory homeostatic plasticity (23). Intrinsic excitability is also homeostatically regulated by activity. Changes in input resistance (Rin) and voltage-activated K⁺ and Na⁺ channel number (24–27), and in Na⁺ channel compartmentalization (28, 29), have been described following manipulations that chronically alter neuronal activity. Finally, in vivo manipulation of neuronal activity with TTX results in larger mEPSC amplitudes and reduced Rin of CA1 pyramidal neurons (30), suggesting that multiple mechanisms of homeostatic plasticity can occur simultaneously in the intact nervous system.Loss of GABAergic interneurons is common across different neurological disorders. It is unknown whether homeostatic plasticity can be induced by changes in activity related to interneuronopathy or how the combination of interneuron cell death and compensation alters circuit function. To begin to address these issues, we studied synaptic and intrinsic excitability in a hippocampal circuit in which a subpopulation of interneurons is reduced [i.e., distal-less homeobox 1 (Dlx1^−/−) mice] (31–33). At around 30 d of age, these mice lose a subset of somatostatin (Sst)-, calretinin (CR)-, vasoactive intestinal peptide-, and neuropeptide Y (NPY)-positive interneurons; exhibit decreased inhibitory synaptic activity in some brain regions; and subsequently develop epilepsy (31). Our results show that secondary to the in vivo interneuron loss is a homeostatic reduction in mEPSC frequency, decreased AMPA/NMDA ratio, and decreased intrinsic excitability in CA1 pyramidal neurons (that do not express Dlx1). Transplantation of GABA progenitor cells from the medial ganglionic eminence (MGE) (34) causes a reversal of the homeostatic changes in excitatory synaptic activity and Rin. Additionally, we describe unique changes in Dlx1^−/− circuit function that homeostatic compensation does not correct: enhanced long-term potentiation (LTP) and altered gamma frequency oscillations (GFOs). The severity of these phenotypes is reduced by interneuron transplantation. These studies demonstrate the responsiveness of excitatory circuitry to changes in inhibition, using homeostatic plasticity as a mechanism for maintaining excitatory/inhibitory balance.     

Differential effect of aneuploidy on the X chromosome and genes with sex-biased expression in Drosophila

Global analysis of gene expression via RNA sequencing was conducted for trisomics for the left arm of chromosome 2 (2L) and compared with the normal genotype. The predominant response of genes on 2L was dosage compensation in that similar expression occurred in the trisomic compared with the diploid control. However, the male and female trisomic/normal expression ratio distributions for 2L genes differed in that females also showed a strong peak of genes with increased expression and males showed a peak of reduced expression relative to the opposite sex. For genes in other autosomal regions, the predominant response to trisomy was reduced expression to the inverse of the altered chromosomal dosage (2/3), but a minor peak of increased expression in females and further reduced expression in males were also found, illustrating a sexual dimorphism for the response to aneuploidy. Moreover, genes with sex-biased expression as revealed by comparing amounts in normal males and females showed responses of greater magnitude to trisomy 2L, suggesting that the genes involved in dosage-sensitive aneuploid effects also influence sex-biased expression. Each autosomal chromosome arm responded to 2L trisomy similarly, but the ratio distributions for X-linked genes were distinct in both sexes, illustrating an X chromosome-specific response to aneuploidy.Changes in chromosomal dosage have long been known to affect the phenotype or viability of an organism (1–4). Altering the dosage of individual chromosomes typically has a greater impact than varying the whole genome (5–7). This general rule led to the concept of “genomic balance” in that dosage changes of part of the genome produce a nonoptimal relationship of gene products. The interpretation afforded these observations was that genes on the aneuploid chromosome produce a dosage effect for the amount of gene product present in the cell (8).However, when gene expression studies were conducted on aneuploids, it became known that transacting modulations of gene product amounts were also more prevalent with aneuploidy than with whole-genome changes (9–14). Assays of enzyme activities, protein, and RNA levels revealed that any one chromosomal segment could modulate in trans the expression of genes throughout the genome (9–15). These modulations could be positively or negatively correlated with the changed chromosomal segment dosage, but inverse correlations were the most common (10–13). For genes on the varied segment, not only were dosage effects observed, but dosage compensation was also observed, which results from a cancelation of gene dosage effects by inverse effects operating simultaneously on the varied genes (9, 10, 14–18). This circumstance results in “autosomal” dosage compensation (14, 16–18). Studies of trisomic X chromosomes examining selected endogenous genes or global RNA sequencing (RNA-seq) studies illustrate that the inverse effect can also account for sex chromosome dosage compensation in Drosophila (15, 19–21). In concert, autosomal genes are largely inversely affected by trisomy of the X chromosome (15, 19, 21).The dosage effects of aneuploidy can be reduced to the action of single genes whose functions tend to be involved in heterogeneous aspects of gene regulation but which have in common membership in macromolecular complexes (8, 22–24). This fact led to the hypothesis that genomic imbalance effects result from the altered stoichiometry of subunits that affects the function of the whole and that occurs from partial but not whole-genome dosage change (8, 22–25). Genomic balance also affects the evolutionary trajectory of duplicate genes differently based on whether the mode of duplication is partial or whole-genome (22, 23).Here we used RNA-seq to examine global patterns of gene expression in male and female larvae trisomic for the left arm of chromosome 2 (2L). The results demonstrate the strong prevalence of aneuploidy dosage compensation and of transacting inverse effects. Furthermore, because both trisomic males and females could be examined, a sexual dimorphism of the aneuploid response was discovered. Also, the response of the X chromosome to trisomy 2L was found to be distinct from that of the autosomes, illustrating an X chromosome-specific effect. Genes with sex-biased expression, as determined by comparing normal males and females, responded more strongly to trisomy 2L. Collectively, the results illustrate the prevalence of the inverse dosage effect in trisomic Drosophila and suggest that the X chromosome has evolved a distinct response to genomic imbalance as would be expected under the hypothesis that X chromosome dosage compensation uses the inverse dosage effect as part of its mechanism (15).     

Dystroglycan mediates homeostatic synaptic plasticity at GABAergic synapses

Dystroglycan (DG), a cell adhesion molecule well known to be essential for skeletal muscle integrity and formation of neuromuscular synapses, is also present at inhibitory synapses in the central nervous system. Mutations that affect DG function not only result in muscular dystrophies, but also in severe cognitive deficits and epilepsy. Here we demonstrate a role of DG during activity-dependent homeostatic regulation of hippocampal inhibitory synapses. Prolonged elevation of neuronal activity up-regulates DG expression and glycosylation, and its localization to inhibitory synapses. Inhibition of protein synthesis prevents the activity-dependent increase in synaptic DG and GABA_A receptors (GABA_ARs), as well as the homeostatic scaling up of GABAergic synaptic transmission. RNAi-mediated knockdown of DG blocks homeostatic scaling up of inhibitory synaptic strength, as does knockdown of like-acetylglucosaminyltransferase (LARGE)—a glycosyltransferase critical for DG function. In contrast, DG is not required for the bicuculline-induced scaling down of excitatory synaptic strength or the tetrodotoxin-induced scaling down of inhibitory synaptic strength. The DG ligand agrin increases GABAergic synaptic strength in a DG-dependent manner that mimics homeostatic scaling up induced by increased activity, indicating that activation of this pathway alone is sufficient to regulate GABA_AR trafficking. These data demonstrate that DG is regulated in a physiologically relevant manner in neurons and that DG and its glycosylation are essential for homeostatic plasticity at inhibitory synapses.Muscular dystrophies are often associated with mild to severe cognitive deficits, epilepsy, and other neurological deficits (1–3). This is particularly evident in muscular dystrophies caused by mutations that affect glycosylation of the membrane glycoprotein α-dystroglycan (α-DG) (4). α-DG docks with transmembrane β-DG to form the functional core of the dystrophin-associated glycoprotein complex (DGC) that links adhesive proteins in the extracellular matrix to dystrophin (5). α-DG is heavily glycosylated and interacts via its carbohydrate side chains with laminin and laminin G-like domains in a variety of proteins including agrin, perlecan, slit, neurexin, and pikachurin (6–10). Key carbohydrate residues are added onto α-DG by several glycosyltransferases, most notably like-acetylglucosaminyltransferase (LARGE) (11). LARGE is necessary for functional glycosylation of α-DG (12), and is mutated in muscular dystrophies associated with severe cognitive deficits (4).DG was first identified in the nervous system (13), where it is important during development for neuroblast migration (14), axon guidance (7), and ribbon synapse formation (8). At neuromuscular synapses, DG is required for the stabilization of acetylcholine receptors in the postsynaptic density and contributes to the accumulation of acetylcholinesterase (10, 15). However, the function of DG at central synapses remains essentially unknown. In the mature central nervous system (CNS), neuronal DGC components are exclusively colocalized with GABA_A receptors (GABA_ARs) in multiple brain regions (16–18), raising the possibility for a role in GABA_AR regulation. However, DG is dispensable for GABAergic synapse formation in hippocampal cultures (17), although adult mice lacking full-length dystrophin show reduced clustering of GABA_ARs in the hippocampus and other brain regions (16, 19, 20). Because dystrophin localization at GABAergic synapses depends on DG (17), these findings suggest that DG may regulate the plasticity of mature GABAergic synapses. Homeostatic synaptic plasticity is widely thought to be essential for brain function and involves the reciprocal regulation of glutamatergic and GABAergic synapses to stabilize neuronal activity (21). Chronic elevation of neuronal activity is associated with an increase in synaptic GABA_ARs (22, 23), but the mechanistic details are incompletely understood.Here, we assess the roles of DG and α-DG glycosylation in regulating the expression of homeostatic synaptic plasticity at GABAergic synapses. We find that in mature hippocampal cultures, prolonged elevation of neuronal activity up-regulates DG expression and the coclustering of α-DG and GABA_ARs. Inhibition of protein synthesis or knockdown of DG blocks homeostatic scaling up of GABAergic synaptic strength. Knockdown of the selective α-DG glycosyltransferase LARGE also blocks homeostatic scaling up, suggesting a role for ligand binding. Furthermore, exogenous application of agrin—a ligand for glycosylated α-DG—is sufficient to scale up GABAergic synaptic strength in a DG-dependent fashion. These data identify a mechanism whereby expression of glycosylated α-DG is linked to neuronal activity level and is essential for homeostatic scaling up of GABAergic synaptic strength by regulating GABA_AR abundance at the synapse.     

Self-assembly of alkynylplatinum(II) terpyridine amphiphiles into nanostructures via steric control and metal–metal interactions

A series of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing the hydrophilic oligo(para-phenylene ethynylene) with two 3,6,9-trioxadec-1-yloxy chains was designed and synthesized. The mononuclear alkynylplatinum(II) terpyridine complex was found to display a very strong tendency toward the formation of supramolecular structures. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would lead to the formation of nanotubes or helical ribbons. These desirable nanostructures were found to be governed by the steric bulk on the platinum(II) terpyridine moieties, which modulates the directional metal−metal interactions and controls the formation of nanotubes or helical ribbons. Detailed analysis of temperature-dependent UV-visible absorption spectra of the nanostructured tubular aggregates also provided insights into the assembly mechanism and showed the role of metal−metal interactions in the cooperative supramolecular polymerization of the amphiphilic platinum(II) complexes.Square-planar d⁸ platinum(II) polypyridine complexes have long been known to exhibit intriguing spectroscopic and luminescence properties (1–54) as well as interesting solid-state polymorphism associated with metal−metal and π−π stacking interactions (1–14, 25). Earlier work by our group showed the first example, to our knowledge, of an alkynylplatinum(II) terpyridine system [Pt(tpy)(C ≡ CR)]⁺ that incorporates σ-donating and solubilizing alkynyl ligands together with the formation of Pt···Pt interactions to exhibit notable color changes and luminescence enhancements on solvent composition change (25) and polyelectrolyte addition (26). This approach has provided access to the alkynylplatinum(II) terpyridine and other related cyclometalated platinum(II) complexes, with functionalities that can self-assemble into metallogels (27–31), liquid crystals (32, 33), and other different molecular architectures, such as hairpin conformation (34), helices (35–38), nanostructures (39–45), and molecular tweezers (46, 47), as well as having a wide range of applications in molecular recognition (48–52), biomolecular labeling (48–52), and materials science (53, 54). Recently, metal-containing amphiphiles have also emerged as a building block for supramolecular architectures (42–44, 55–59). Their self-assembly has always been found to yield different molecular architectures with unprecedented complexity through the multiple noncovalent interactions on the introduction of external stimuli (42–44, 55–59).Helical architecture is one of the most exciting self-assembled morphologies because of the uniqueness for the functional and topological properties (60–69). Helical ribbons composed of amphiphiles, such as diacetylenic lipids, glutamates, and peptide-based amphiphiles, are often precursors for the growth of tubular structures on an increase in the width or the merging of the edges of ribbons (64, 65). Recently, the optimization of nanotube formation vs. helical nanostructures has aroused considerable interests and can be achieved through a fine interplay of the influence on the amphiphilic property of molecules (66), choice of counteranions (67, 68), or pH values of the media (69), which would govern the self-assembly of molecules into desirable aggregates of helical ribbons or nanotube scaffolds. However, a precise control of supramolecular morphology between helical ribbons and nanotubes remains challenging, particularly for the polycyclic aromatics in the field of molecular assembly (64–69). Oligo(para-phenylene ethynylene)s (OPEs) with solely π−π stacking interactions are well-recognized to self-assemble into supramolecular system of various nanostructures but rarely result in the formation of tubular scaffolds (70–73). In view of the rich photophysical properties of square-planar d⁸ platinum(II) systems and their propensity toward formation of directional Pt···Pt interactions in distinctive morphologies (27–31, 39–45), it is anticipated that such directional and noncovalent metal−metal interactions might be capable of directing or dictating molecular ordering and alignment to give desirable nanostructures of helical ribbons or nanotubes in a precise and controllable manner.Herein, we report the design and synthesis of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing hydrophilic OPEs with two 3,6,9-trioxadec-1-yloxy chains. The mononuclear alkynylplatinum(II) terpyridine complex with amphiphilic property is found to show a strong tendency toward the formation of supramolecular structures on diffusion of diethyl ether in dichloromethane or dimethyl sulfoxide (DMSO) solution. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would result in nanotubes or helical ribbons in the self-assembly process. To the best of our knowledge, this finding represents the first example of the utilization of the steric bulk of the moieties, which modulates the formation of directional metal−metal interactions to precisely control the formation of nanotubes or helical ribbons in the self-assembly process. Application of the nucleation–elongation model into this assembly process by UV-visible (UV-vis) absorption spectroscopic studies has elucidated the nature of the molecular self-assembly, and more importantly, it has revealed the role of metal−metal interactions in the formation of these two types of nanostructures.     

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.     

Potentiation of cytotoxic chemotherapy by growth hormone-releasing hormone agonists

The dismal prognosis of malignant brain tumors drives the development of new treatment modalities. In view of the multiple activities of growth hormone-releasing hormone (GHRH), we hypothesized that pretreatment with a GHRH agonist, JI-34, might increase the susceptibility of U-87 MG glioblastoma multiforme (GBM) cells to subsequent treatment with the cytotoxic drug, doxorubicin (DOX). This concept was corroborated by our findings, in vivo, showing that the combination of the GHRH agonist, JI-34, and DOX inhibited the growth of GBM tumors, transplanted into nude mice, more than DOX alone. In vitro, the pretreatment of GBM cells with JI-34 potentiated inhibitory effects of DOX on cell proliferation, diminished cell size and viability, and promoted apoptotic processes, as shown by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide proliferation assay, ApoLive-Glo multiplex assay, and cell volumetric assay. Proteomic studies further revealed that the pretreatment with GHRH agonist evoked differentiation decreasing the expression of the neuroectodermal stem cell antigen, nestin, and up-regulating the glial maturation marker, GFAP. The GHRH agonist also reduced the release of humoral regulators of glial growth, such as FGF basic and TGFβ. Proteomic and gene-expression (RT-PCR) studies confirmed the strong proapoptotic activity (increase in p53, decrease in v-myc and Bcl-2) and anti-invasive potential (decrease in integrin α3) of the combination of GHRH agonist and DOX. These findings indicate that the GHRH agonists can potentiate the anticancer activity of the traditional chemotherapeutic drug, DOX, by multiple mechanisms including the induction of differentiation of cancer cells.Glioblastoma multiforme (GBM) is one of the most aggressive human cancers, and the afflicted patients inevitably succumb. The dismal outcome of this malignancy demands great efforts to find improved methods of treatment (1). Many compounds have been synthesized in our laboratory in the past few years that have proven to be effective against diverse malignant tumors (2–14). These are peptide analogs of hypothalamic hormones: luteinizing hormone-releasing hormone (LHRH), growth hormone-releasing hormone (GHRH), somatostatin, and analogs of other neuropeptides such as bombesin and gastrin-releasing peptide. The receptors for these peptides have been found to be widely distributed in the human body, including in many types of cancers (2–14). The regulatory functions of these hypothalamic hormones and other neuropeptides are not confined to the hypothalamo–hypophyseal system or, even more broadly, to the central nervous system (CNS). In particular, GHRH can induce the differentiation of ovarian granulosa cells and other cells in the reproductive system and function as a growth factor in various normal tissues, benign tumors, and malignancies (2–4, 6, 11, 14–18). Previously, we also reported that antagonistic cytototoxic derivatives of some of these neuropeptides are able to inhibit the growth of several malignant cell lines (2–14).Our earlier studies showed that treatment with antagonists of LHRH or GHRH rarely effects complete regression of glioblastoma-derived tumors (5, 7, 10, 11). Previous studies also suggested that growth factors such as EGF or agonistic analogs of LHRH serving as carriers for cytotoxic analogs and functioning as growth factors may sensitize cancer cells to cytotoxic treatments (10, 19) through the activation of maturation processes. We therefore hypothesized that pretreatment with one of our GHRH agonists, such as JI-34 (20), which has shown effects on growth and differentiation in other cell lines (17, 18, 21, 22), might decrease the pluripotency and the adaptability of GBM cells and thereby increase their susceptibility to cytotoxic treatment.In vivo, tumor cells were implanted into athymic nude mice, tumor growth was recorded weekly, and final tumor mass was measured upon autopsy. In vitro, proliferation assays were used for the determination of neoplastic proliferation and cell growth. Changes in stem (nestin) and maturation (GFAP) antigen expression was evaluated with Western blot studies in vivo and with immunocytochemistry in vitro. The production of glial growth factors (FGF basic, TGFβ) was verified by ELISA. Further, using the Human Cancer Pathway Finder real-time quantitative PCR, numerous genes that play a role in the development of cancer were evaluated. We placed particular emphasis on the measurement of apoptosis, using the ApoLive-Glo Multiplex Assay kit and by detection of the expression of the proapoptotic p53 protein. This overall approach permitted the evaluation of the effect of GHRH agonist, JI-34, on the response to chemotherapy with doxorubicin.     

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.     

Tonic GABAA conductance bidirectionally controls interneuron firing pattern and synchronization in the CA3 hippocampal network

The spiking output of interneurons is key for rhythm generation in the brain. However, what controls interneuronal firing remains incompletely understood. Here we combine dynamic clamp experiments with neural network simulations to understand how tonic GABA_A conductance regulates the firing pattern of CA3 interneurons. In baseline conditions, tonic GABA_A depolarizes these cells, thus exerting an excitatory action while also reducing the excitatory postsynaptic potential (EPSP) amplitude through shunting. As a result, the emergence of weak tonic GABA_A conductance transforms the interneuron firing pattern driven by individual EPSPs into a more regular spiking mode determined by the cell intrinsic properties. The increased regularity of spiking parallels stronger synchronization of the local network. With further increases in tonic GABA_A conductance the shunting inhibition starts to dominate over excitatory actions and thus moderates interneuronal firing. The remaining spikes tend to follow the timing of suprathreshold EPSPs and thus become less regular again. The latter parallels a weakening in network synchronization. Thus, our observations suggest that tonic GABA_A conductance can bidirectionally control brain rhythms through changes in the excitability of interneurons and in the temporal structure of their firing patterns.Rhythmic activity paces signal transfer within brain circuits. Brain rhythms are believed to depend heavily on the networks of inhibitory interneurons (1–4). In addition to synaptic inputs, interneuron excitability in the hippocampus is determined by tonic GABA_A conductance (5, 6), which could thus contribute to hippocampal rhythmogenesis. Indeed, GABA transaminase inhibitor vigabatrin increases the ambient GABA concentration, enhancing the power of the theta-rhythm in rats (7). In mice expressing GFP under the GAD67 promoter the reduced levels of ambient GABA correlate with a decreased power of kainate-induced oscillations in vitro (8). The latter decrease is reversed by a GABA uptake inhibitor, guvacine, which raises ambient GABA. GABA release by astrocytes also increases the gamma oscillation power in hippocampal area CA1 in vivo (9). Intriguingly, in hippocampal slices of animals lacking δ subunit-containing GABA_A receptors (which mediate tonic conductance in many local cell types including interneurons) the average frequency of cholinergically induced gamma oscillations is increased, whereas the oscillation power tends to drop (10). However, cellular mechanisms underlying such phenomena remain poorly understood.One possible explanation is the influence of tonic GABA_A conductance on the firing pattern of interneurons. Activation of GABA_A receptors inhibits most neurons, through either membrane hyperpolarization or shunting or both (11). In the adult brain, a depolarizing action of GABA has also been reported in various cell types, including hippocampal interneurons (3, 12–15). GABAergic depolarization can prompt spike generation, thus countering the shunting effects (14, 16). Therefore, experimental evidence indicates that the net effect of GABA_A receptor activation combines the excitatory action of depolarization and the inhibitory consequences of shunting, with the latter prevailing when the GABA_A receptor conductance is sufficiently strong. As a result, increasing the tonic GABA_A signaling can have a biphasic effect on individual hippocampal interneurons: excitatory at weak conductances and inhibitory at strong (14). Here we find that weak tonic GABA_A conductance favors a more regular firing pattern of interneurons, thus facilitating synchronization of the CA3 network. In contrast, strong GABA_A conductance makes the firing pattern more dependent on the stochastic excitatory synaptic input, thus reducing network synchrony.     

Stochastic transitions into silence cause noise correlations in cortical circuits

The spiking activity of cortical neurons is highly variable. This variability is generally correlated among nearby neurons, an effect commonly interpreted to reflect the coactivation of neurons due to anatomically shared inputs. Recent findings, however, indicate that correlations can be dynamically modulated, suggesting that the underlying mechanisms are not well understood. Here, we investigate the hypothesis that correlations are dominated by neuronal coinactivation: the occurrence of brief silent periods during which all neurons in the local network stop firing. We recorded spiking activity from large populations of neurons in the auditory cortex of anesthetized rats across different brain states. During spontaneous activity, the reduction of correlation accompanying brain state desynchronization was largely explained by a decrease in the density of the silent periods. The presentation of a stimulus caused an initial drop of correlations followed by a rebound, a time course that was mimicked by the instantaneous silence density. We built a rate network model with fluctuation-driven transitions between a silent and an active attractor and assumed that neurons fired Poisson spike trains with a rate following the model dynamics. Variations of the network external input altered the transition rate into the silent attractor and reproduced the relation between correlation and silence density found in the data, both in spontaneous and evoked conditions. This suggests that the observed changes in correlation, occurring gradually with brain state variations or abruptly with sensory stimulation, are due to changes in the likeliness of the microcircuit to transiently cease firing.Neuronal noise correlations are defined as common fluctuations in the spiking activity of neurons under conditions of constant sensory input or motor output. Traditionally, they have been thought to arise from the dense connectivity of the cortex, such that neighboring neurons sharing a fraction of their inputs should also share a fraction of their output variability (1). Several observations are consistent with this hypothesis: pairwise correlations in the cortex decrease with cell pair distance (2) or with the difference in stimulus selectivity (3), dependencies that could follow from a variation in shared input given the anatomy of cortical circuits. Recent findings, however, challenge this simple interpretation. Recordings in the primate visual cortex have shown that attention or task context can change correlation structure (4–6) and that the magnitude of averaged correlation can be very low (7). In anesthetized rodents correlations decrease with brain state desynchronization (8, 9) or when animals switch from quiet wakefulness to active whisking during waking (10). Moreover, the commonly observed drop of spiking variability following stimulus onset (11–13) seems to occur jointly with a transient decrease in correlation (2, 14, 15). These observations suggest that correlations reflect the dynamical state of the circuit more than its hardwired connectivity.Despite substantial progress in understanding the mechanisms giving rise to large individual variability in recurrent networks (9, 16–18), we still lack a canonical model that can generate correlations with the same magnitude and spatiotemporal structure as those observed in cortical circuits. Balanced networks, for instance, a common model that reproduces the large variability of cortical neurons (9, 18, 19), show near-zero averaged correlations (9). Numerous studies have investigated the generation of synchronous firing (20), but whether short bursts of population activity can quantitatively account for the spike count correlations found in the data is unclear. Recurrent networks can also generate fast oscillations in the population activity, but, in a regime of low rates, typical of cortical circuits, average spike count correlations are negligible (21). Network models producing nonzero average correlations are those exhibiting up and down dynamics (22–29). Most of these studies have focused on investigating the mechanisms underlying the slow oscillatory activity observed in cortical slices (30), under anesthesia (31, 32), or during slow-wave sleep (33). Only recently the impact of up and down switching on trial-to-trial response variability (25) and on the probability distribution of multiunit activity (29) across brain states has been investigated. Whether the alternation between up and down phases could quantitatively account for the pairwise correlations observed in different brain states and describe their stimulus-evoked dynamics remains an open question.To investigate the mechanisms producing correlated firing, we recorded the spiking activity of large populations of neurons from the auditory cortex of anesthetized rats. During spontaneous activity, changes in correlation were largely explained by variation of the occurrence rate of periods during which neurons in the circuit stopped firing. Furthermore, the time course of correlation in response to an acoustic stimulus reflected the transient variation of this silence density. A computational rate model with fluctuation-driven transitions between silent and active attractors could explain the experimentally observed time course of correlation and its relation to silence density. Our findings suggest that the dynamics of these transitions play a fundamental role in generating noise correlations among cortical neurons.     

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-μs MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein–solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.Proteins explore many conformations while carrying out their functions in biological systems (1–3). X-ray crystallography is the dominant source of information about protein structure; however, crystal structure models usually consist of just a single major conformation and at most a small portion of the model as alternate conformations. Crystal structures therefore are missing many details about the underlying conformational ensemble (4).Proteins assembled in crystalline arrays, like proteins in solution, exhibit rich conformational diversity (4) and often can perform their native functions (5). Many methods have emerged for using Bragg data to model conformational diversity in protein crystals (6–17). The development of these methods has been important as conformational diversity can lead to inaccuracies in protein structure models (9, 18–20). A key limitation of using the Bragg data, however, is that different models of conformational diversity can yield the same mean electron density.Whereas the Bragg scattering only contains information about the mean electron density, diffuse scattering (diffraction resulting in intensity between the Bragg peaks) is sensitive to spatial correlations in electron density variations (21–28) and therefore contains information about the way that atomic positions vary together in protein crystals. Because models that yield the same mean electron density can yield different correlations in electron density variations, diffuse scattering provides a means to increase the accuracy of crystallography for determining protein conformational variations (29). Peter Moore (30) and Mark Wilson (31) have argued that diffuse scattering should be used to test models of conformational diversity in X-ray crystallography.Several pioneering studies used diffuse scattering to reveal insights into correlated motions in proteins (17, 30, 32–49). Some of these studies used diffuse scattering to experimentally validate predictions of correlated motions from molecular-dynamics (MD) simulations (35–37, 40, 42–44). These studies revealed important insights but were limited by inadequate sampling of the conformational ensemble, leading to lack of convergence of the diffuse scattering calculations (35). Microsecond-scale simulations of staphylococcal nuclease were predicted to be adequate for convergence of diffuse scattering calculations (42). Modern simulation algorithms and computer hardware now enable microsecond or longer MD simulations of protein crystals (50).Here, we present calculations of diffuse X-ray scattering using a 1.1-μs MD simulation of crystalline staphylococcal nuclease. The results demonstrate that we have overcome the past limitation of inadequate sampling. We chose staphylococcal nuclease because the experiments of Wall et al. (49) still represent the only complete, high-quality, 3D diffuse scattering data set from a protein crystal. The calculated diffuse intensity is very similar using two independent halves of the trajectory; the results therefore are reproducible and can be meaningfully compared with the experimental data. The MD simulation provides a rich picture of conformational diversity in the energy landscape of a protein crystal, consisting of at least eight metastable states. Like previous MD studies of crystalline staphylococcal nuclease (42–44), the agreement of the simulation with the total experimental diffuse intensity is excellent, supporting the use of MD simulations to model diffuse scattering data. Unlike previous MD studies, we separately compared the more finely structured, anisotropic component of the diffuse intensity with experimental data. The agreement is substantial but weaker than for the isotropic component, indicating there are inaccuracies in the MD models. Our results therefore point toward using diffuse scattering to improve MD models of protein motions.     

The evolution of self-control

Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.Since Darwin, understanding the evolution of cognition has been widely regarded as one of the greatest challenges for evolutionary research (1). Although researchers have identified surprising cognitive flexibility in a range of species (2–40) and potentially derived features of human psychology (41–61), we know much less about the major forces shaping cognitive evolution (62–71). With the notable exception of Bitterman’s landmark studies conducted several decades ago (63, 72–74), most research comparing cognition across species has been limited to small taxonomic samples (70, 75). With limited comparable experimental data on how cognition varies across species, previous research has largely relied on proxies for cognition (e.g., brain size) or metaanalyses when testing hypotheses about cognitive evolution (76–92). The lack of cognitive data collected with similar methods across large samples of species precludes meaningful species comparisons that can reveal the major forces shaping cognitive evolution across species, including humans (48, 70, 89, 93–98).To address these challenges we measured cognitive skills for self-control in 36 species of mammals and birds (Fig. 1 and Tables S1–S4) tested using the same experimental procedures, and evaluated the leading hypotheses for the neuroanatomical underpinnings and ecological drivers of variance in animal cognition. At the proximate level, both absolute (77, 99–107) and relative brain size (108–112) have been proposed as mechanisms supporting cognitive evolution. Evolutionary increases in brain size (both absolute and relative) and cortical reorganization are hallmarks of the human lineage and are believed to index commensurate changes in cognitive abilities (52, 105, 113–115). Further, given the high metabolic costs of brain tissue (116–121) and remarkable variance in brain size across species (108, 122), it is expected that the energetic costs of large brains are offset by the advantages of improved cognition. The cortical reorganization hypothesis suggests that selection for absolutely larger brains—and concomitant cortical reorganization—was the predominant mechanism supporting cognitive evolution (77, 91, 100–106, 120). In contrast, the encephalization hypothesis argues that an increase in brain volume relative to body size was of primary importance (108, 110, 111, 123). Both of these hypotheses have received support through analyses aggregating data from published studies of primate cognition and reports of “intelligent” behavior in nature—both of which correlate with measures of brain size (76, 77, 84, 92, 110, 124).Open in a separate windowFig. 1.A phylogeny of the species included in this study. Branch lengths are proportional to time except where long branches have been truncated by parallel diagonal lines (split between mammals and birds ∼292 Mya).With respect to selective pressures, both social and dietary complexities have been proposed as ultimate causes of cognitive evolution. The social intelligence hypothesis proposes that increased social complexity (frequently indexed by social group size) was the major selective pressure in primate cognitive evolution (6, 44, 48, 50, 87, 115, 120, 125–141). This hypothesis is supported by studies showing a positive correlation between a species’ typical group size and the neocortex ratio (80, 81, 85–87, 129, 142–145), cognitive differences between closely related species with different group sizes (130, 137, 146, 147), and evidence for cognitive convergence between highly social species (26, 31, 148–150). The foraging hypothesis posits that dietary complexity, indexed by field reports of dietary breadth and reliance on fruit (a spatiotemporally distributed resource), was the primary driver of primate cognitive evolution (151–154). This hypothesis is supported by studies linking diet quality and brain size in primates (79, 81, 86, 142, 155), and experimental studies documenting species differences in cognition that relate to feeding ecology (94, 156–166).Although each of these hypotheses has received empirical support, a comparison of the relative contributions of the different proximate and ultimate explanations requires (i) a cognitive dataset covering a large number of species tested using comparable experimental procedures; (ii) cognitive tasks that allow valid measurement across a range of species with differing morphology, perception, and temperament; (iii) a representative sample within each species to obtain accurate estimates of species-typical cognition; (iv) phylogenetic comparative methods appropriate for testing evolutionary hypotheses; and (v) unprecedented collaboration to collect these data from populations of animals around the world (70).Here, we present, to our knowledge, the first large-scale collaborative dataset and comparative analysis of this kind, focusing on the evolution of self-control. We chose to measure self-control—the ability to inhibit a prepotent but ultimately counterproductive behavior—because it is a crucial and well-studied component of executive function and is involved in diverse decision-making processes (167–169). For example, animals require self-control when avoiding feeding or mating in view of a higher-ranking individual, sharing food with kin, or searching for food in a new area rather than a previously rewarding foraging site. In humans, self-control has been linked to health, economic, social, and academic achievement, and is known to be heritable (170–172). In song sparrows, a study using one of the tasks reported here found a correlation between self-control and song repertoire size, a predictor of fitness in this species (173). In primates, performance on a series of nonsocial self-control control tasks was related to variability in social systems (174), illustrating the potential link between these skills and socioecology. Thus, tasks that quantify self-control are ideal for comparison across taxa given its robust behavioral correlates, heritable basis, and potential impact on reproductive success.In this study we tested subjects on two previously implemented self-control tasks. In the A-not-B task (27 species, n = 344), subjects were first familiarized with finding food in one location (container A) for three consecutive trials. In the test trial, subjects initially saw the food hidden in the same location (container A), but then moved to a new location (container B) before they were allowed to search (Movie S1). In the cylinder task (32 species, n = 439), subjects were first familiarized with finding a piece of food hidden inside an opaque cylinder. In the following 10 test trials, a transparent cylinder was substituted for the opaque cylinder. To successfully retrieve the food, subjects needed to inhibit the impulse to reach for the food directly (bumping into the cylinder) in favor of the detour response they had used during the familiarization phase (Movie S2).Thus, the test trials in both tasks required subjects to inhibit a prepotent motor response (searching in the previously rewarded location or reaching directly for the visible food), but the nature of the correct response varied between tasks. Specifically, in the A-not-B task subjects were required to inhibit the response that was previously successful (searching in location A) whereas in the cylinder task subjects were required to perform the same response as in familiarization trials (detour response), but in the context of novel task demands (visible food directly in front of the subject).     

Cellular heterogeneity profiling by hyaluronan probes reveals an invasive but slow-growing breast tumor subset

Tumor heterogeneity confounds cancer diagnosis and the outcome of therapy, necessitating analysis of tumor cell subsets within the tumor mass. Elevated expression of hyaluronan (HA) and HA receptors, receptor for HA-mediated motility (RHAMM)/HA-mediated motility receptor and cluster designation 44 (CD44), in breast tumors correlates with poor outcome. We hypothesized that a probe for detecting HA–HA receptor interactions may reveal breast cancer (BCa) cell heterogeneity relevant to tumor progression. A fluorescent HA (F-HA) probe containing a mixture of polymer sizes typical of tumor microenvironments (10–480 kDa), multiplexed profiling, and flow cytometry were used to monitor HA binding to BCa cell lines of different molecular subtypes. Formulae were developed to quantify binding heterogeneity and to measure invasion in vivo. Two subsets exhibiting differential binding (HA^−/low vs. HA^high) were isolated and characterized for morphology, growth, and invasion in culture and as xenografts in vivo. F-HA–binding amounts and degree of heterogeneity varied with BCa subtype, were highest in the malignant basal-like cell lines, and decreased upon reversion to a nonmalignant phenotype. Binding amounts correlated with CD44 and RHAMM displayed but binding heterogeneity appeared to arise from a differential ability of HA receptor-positive subpopulations to interact with F-HA. HA^high subpopulations exhibited significantly higher local invasion and lung micrometastases but, unexpectedly, lower proliferation than either unsorted parental cells or the HA^−/low subpopulation. Querying F-HA binding to aggressive tumor cells reveals a previously undetected form of heterogeneity that predicts invasive/metastatic behavior and that may aid both early identification of cancer patients susceptible to metastasis, and detection/therapy of invasive BCa subpopulations.Breast tumors display substantial heterogeneity driven by genetic and epigenetic mechanisms (1–3). These processes select and support tumor cell subpopulations with distinct phenotypes in proliferation, metastatic/invasive proclivity, and treatment susceptibility that contribute to clinical outcomes. Currently, there is a paucity of biomarkers to identify these subpopulations (3–12). Although detection of genetic heterogeneity may itself be a breast cancer (BCa) prognostic marker (3, 13–15), the phenotypes manifested from this diversity are context-dependent. Therefore, phenotypic markers provide additional powerful tools for biological information required to design diagnostics and therapeutics. Glycomic approaches have enormous potential for revealing tumor cell phenotypic heterogeneity because glycans are themselves highly heterogeneous and their complexity reflects the nutritional, microenvironmental, and genetic dynamics of the tumors (16–18).We used hyaluronan (HA) as a model carbohydrate ligand for probing heterogeneity in glycosaminoglycan–BCa cell receptor interactions. We reasoned this approach would reveal previously undetected cellular and functional heterogeneity linked to malignant progression because the diversity of cell glycosylation patterns, which can occur as covalent and noncovalent modifications of proteins and lipids as well as different sizes of such polysaccharides as HA, is unrivaled (16, 17, 19). In particular, tumor and wound microenvironments contain different sizes of HA polymers that bind differentially to cell receptors to activate signaling pathways regulating cell migration, invasion, survival, and proliferation (19–22).More than other related glycosaminoglycans, HA accumulation within BCa tumor cells and peritumor stroma is a predictor of poor outcome (23) and of the conversion of the preinvasive form of BCa, ductal carcinoma in situ, to an early invasive form of BCa (24). HA is a nonantigenic and large, relatively simple, unbranched polymer, but the manner in which it is metabolized is highly complex (19, 25). There are literally thousands of different HA sizes in remodeling microenvironments, including tumors. HA polymers bind to cells via at least six known receptors (16, 19, 20, 26–32). Two of these, cluster designation 44 (CD44) and receptor for HA-mediated motility/HA-mediated motility receptor (RHAMM/HMMR), form multivalent complexes with different ranges of HA sizes (19, 29, 33), and both receptors are implicated in BCa progression (19–21, 23, 29, 30, 33–36). Elevated CD44 expression in the peritumor stroma is associated with increased relapse (37), and in primary BCa cell subsets may contribute to tumor initiation and progression (38–40). Elevated RHAMM expression in BCa tumor subsets is a prognostic indicator of poor outcome and increased metastasis (22, 33, 41). RHAMM polymorphisms may also be a factor in BCa susceptibility (42, 43).We postulated that multivalent interactions resulting from mixture of a polydisperse population of fluorescent HA (F-HA) sizes, typical of those found in remodeling microenvironments of wounds and tumors (19, 20, 29), with cellular HA receptors would uncover a heterogeneous binding pattern useful for sorting tumor cells into distinct subsets. We interrogated the binding of F-HA to BCa lines of different molecular subtypes, and related binding/uptake patterns to CD44 and RHAMM display, and to tumor cell growth, invasion, and metastasis.     

Luminescence color switching of supramolecular assemblies of discrete molecular decanuclear gold(I) sulfido complexes

A series of discrete decanuclear gold(I) μ₃-sulfido complexes with alkyl chains of various lengths on the aminodiphosphine ligands, [Au₁₀{Ph₂PN(C_nH_2n+1)PPh₂}₄(μ₃-S)₄](ClO₄)₂, has been synthesized and characterized. These complexes have been shown to form supramolecular nanoaggregate assemblies upon solvent modulation. The photoluminescence (PL) colors of the nanoaggregates can be switched from green to yellow to red by varying the solvent systems from which they are formed. The PL color variation was investigated and correlated with the nanostructured morphological transformation from the spherical shape to the cube as observed by transmission electron microscopy and scanning electron microscopy. Such variations in PL colors have not been observed in their analogous complexes with short alkyl chains, suggesting that the long alkyl chains would play a key role in governing the supramolecular nanoaggregate assembly and the emission properties of the decanuclear gold(I) sulfido complexes. The long hydrophobic alkyl chains are believed to induce the formation of supramolecular nanoaggregate assemblies with different morphologies and packing densities under different solvent systems, leading to a change in the extent of Au(I)–Au(I) interactions, rigidity, and emission properties.Gold(I) complexes are one of the fascinating classes of complexes that reveal photophysical properties that are highly sensitive to the nuclearity of the metal centers and the metal–metal distances (1–59). In a certain sense, they bear an analogy or resemblance to the interesting classes of metal nanoparticles (NPs) (60–69) and quantum dots (QDs) (70–76) in that the properties of the nanostructured materials also show a strong dependence on their sizes and shapes. Interestingly, while the optical and spectroscopic properties of metal NPs and QDs show a strong dependence on the interparticle distances, those of polynuclear gold(I) complexes are known to mainly depend on the nuclearity and the internuclear separations of gold(I) centers within the individual molecular complexes or clusters, with influence of the intermolecular interactions between discrete polynuclear molecular complexes relatively less explored (34–38), and those of polynuclear gold(I) clusters not reported. Moreover, while studies on polynuclear gold(I) complexes or clusters are known (34–54), less is explored of their hierarchical assembly and nanostructures as well as the influence of intercluster aggregation on the optical properties (34–38). Among the gold(I) complexes, polynuclear gold(I) chalcogenido complexes represent an important and interesting class (44–51). While directed supramolecular assembly of discrete Au₁₂ (52), Au₁₆ (53), Au₁₈ (51), and Au₃₆ (54) metallomacrocycles as well as trinuclear gold(I) columnar stacks (34–38) have been reported, there have been no corresponding studies on the supramolecular hierarchical assembly of polynuclear gold(I) chalcogenido clusters.Based on our interests and experience in the study of gold(I) chalcogenido clusters (44–46, 51), it is believed that nanoaggegrates with interesting luminescence properties and morphology could be prepared by the judicious design of the gold(I) chalcogenido clusters. As demonstrated by our previous studies on the aggregation behavior of square-planar platinum(II) complexes (77–80) where an enhancement of the solubility of the metal complexes via introduction of solubilizing groups on the ligands and the fine control between solvophobicity and solvophilicity of the complexes would have a crucial influence on the factors governing supramolecular assembly and the formation of aggregates (80), introduction of long alkyl chains as solubilizing groups in the gold(I) sulfido clusters may serve as an effective way to enhance the solubility of the gold(I) clusters for the construction of supramolecular assemblies of novel luminescent nanoaggegrates.Herein, we report the preparation and tunable spectroscopic properties of a series of decanuclear gold(I) μ₃-sulfido complexes with alkyl chains of different lengths on the aminophosphine ligands, [Au₁₀{Ph₂PN(C_nH_2n+1)PPh₂}₄(μ₃-S)₄](ClO₄)₂ [n = 8 (1), 12 (2), 14 (3), 18 (4)] and their supramolecular assembly to form nanoaggregates. The emission colors of the nanoaggregates of 2−4 can be switched from green to yellow to red by varying the solvent systems from which they are formed. These results have been compared with their short alkyl chain-containing counterparts, 1 and a related [Au₁₀{Ph₂PN(C₃H₇)PPh₂}₄(μ₃-S)₄](ClO₄)₂ (45). The present work demonstrates that polynuclear gold(I) chalcogenides, with the introduction of appropriate functional groups, can serve as building blocks for the construction of novel hierarchical nanostructured materials with environment-responsive properties, and it represents a rare example in which nanoaggregates have been assembled with the use of discrete molecular metal clusters as building blocks.