Self-assembly of amphiphilic Janus dendrimers into uniform onion-like dendrimersomes with predictable size and number of bilayers

A constitutional isomeric library synthesized by a modular approach has been used to discover six amphiphilic Janus dendrimer primary structures, which self-assemble into uniform onion-like vesicles with predictable dimensions and number of internal bilayers. These vesicles, denoted onion-like dendrimersomes, are assembled by simple injection of a solution of Janus dendrimer in a water-miscible solvent into water or buffer. These dendrimersomes provide mimics of double-bilayer and multibilayer biological membranes with dimensions and number of bilayers predicted by the Janus compound concentration in water. The simple injection method of preparation is accessible without any special equipment, generating uniform vesicles, and thus provides a promising tool for fundamental studies as well as technological applications in nanomedicine and other fields.Most living organisms contain single-bilayer membranes composed of lipids, glycolipids, cholesterol, transmembrane proteins, and glycoproteins (1). Gram-negative bacteria (2, 3) and the cell nucleus (4), however, exhibit a strikingly special envelope that consists of a concentric double-bilayer membrane. More complex membranes are also encountered in cells and their various organelles, such as multivesicular structures of eukaryotic cells (5) and endosomes (6), and multibilayer structures of endoplasmic reticulum (7, 8), myelin (9, 10), and multilamellar bodies (11, 12). This diversity of biological membranes inspired corresponding biological mimics. Liposomes (Fig. 1) self-assembled from phospholipids are the first mimics of single-bilayer biological membranes (13–16), but they are polydisperse, unstable, and permeable (14). Stealth liposomes coassembled from phospholipids, cholesterol, and phospholipids conjugated with poly(ethylene glycol) exhibit improved stability, permeability, and mechanical properties (17–20). Polymersomes (21–24) assembled from amphiphilic block copolymers exhibit better mechanical properties and permeability, but are not always biocompatible and are polydisperse. Dendrimersomes (25–28) self-assembled from amphiphilic Janus dendrimers and minidendrimers (26–28) have also been elaborated to mimic single-bilayer biological membranes. Amphiphilic Janus dendrimers take advantage of multivalency both in their hydrophobic and hydrophilic parts (23, 29–32). Dendrimersomes are assembled by simple injection (33) of a solution of an amphiphilic Janus dendrimer (26) in a water-soluble solvent into water or buffer and produce uniform (34), impermeable, and stable vesicles with excellent mechanical properties. In addition, their size and properties can be predicted by their primary structure (27). Amphiphilic Janus glycodendrimers self-assemble into glycodendrimersomes that mimic the glycan ligands of biological membranes (35). They have been demonstrated to be bioactive toward biomedically relevant bacterial, plant, and human lectins, and could have numerous applications in nanomedicine (20).Open in a separate windowFig. 1.Strategies for the preparation of single-bilayer vesicles and multibilayer onion-like vesicles.More complex and functional cell mimics such as multivesicular vesicles (36, 37) and multibilayer onion-like vesicles (38–40) have also been discovered. Multivesicular vesicles compartmentalize a larger vesicle (37) whereas multibilayer onion-like vesicles consist of concentric alternating bilayers (40). Currently multibilayer vesicles are obtained by very complex and time-consuming methods that do not control their size (39) and size distribution (40) in a precise way. Here we report the discovery of “single–single” (28) amphiphilic Janus dendrimer primary structures that self-assemble into uniform multibilayer onion-like dendrimersomes (Fig. 1) with predictable size and number of bilayers by simple injection of their solution into water or buffer.     

De novo production of the plant-derived alkaloid strictosidine in yeast

The monoterpene indole alkaloids are a large group of plant-derived specialized metabolites, many of which have valuable pharmaceutical or biological activity. There are ∼3,000 monoterpene indole alkaloids produced by thousands of plant species in numerous families. The diverse chemical structures found in this metabolite class originate from strictosidine, which is the last common biosynthetic intermediate for all monoterpene indole alkaloid enzymatic pathways. Reconstitution of biosynthetic pathways in a heterologous host is a promising strategy for rapid and inexpensive production of complex molecules that are found in plants. Here, we demonstrate how strictosidine can be produced de novo in a Saccharomyces cerevisiae host from 14 known monoterpene indole alkaloid pathway genes, along with an additional seven genes and three gene deletions that enhance secondary metabolism. This system provides an important resource for developing the production of more complex plant-derived alkaloids, engineering of nonnatural derivatives, identification of bottlenecks in monoterpene indole alkaloid biosynthesis, and discovery of new pathway genes in a convenient yeast host.Monoterpene indole alkaloids (MIAs) are a diverse family of complex nitrogen-containing plant-derived metabolites (1, 2). This metabolite class is found in thousands of plant species from the Apocynaceae, Loganiaceae, Rubiaceae, Icacinaceae, Nyssaceae, and Alangiaceae plant families (2, 3). Many MIAs and MIA derivatives have medicinal properties; for example, vinblastine, vincristine, and vinflunine are approved anticancer therapeutics (4, 5). These structurally complex compounds can be difficult to chemically synthesize (6, 7). Consequently, industrial production relies on extraction from the plant, but these compounds are often produced in small quantities as complex mixtures, making isolation challenging, laborious, and expensive (8–10). Reconstitution of plant pathways in microbial hosts is proving to be a promising approach to access plant-derived compounds as evidenced by the successful production of terpenes, flavonoids, and benzylisoquinoline alkaloids in microorganisms (11–19). Microbial hosts can also be used to construct hybrid biosynthetic pathways to generate modified natural products with potentially enhanced bioactivities (8, 20, 21). Across numerous plant species, strictosidine is believed to be the core scaffold from which all 3,000 known MIAs are derived (1, 2). Strictosidine undergoes a variety of redox reactions and rearrangements to form the thousands of compounds that comprise the MIA natural product family (Fig. 1) (1, 2). Due to the importance of strictosidine, the last common biosynthetic intermediate for all known MIAs, we chose to focus on heterologous production of this complex molecule (1). Therefore, strictosidine reconstitution represents the necessary first step for heterologous production of high-value MIAs.Open in a separate windowFig. 1.Strictosidine, the central intermediate in monoterpene indole alkaloid (MIA) biosynthesis, undergoes a series of reactions to produce over 3,000 known MIAs such as vincristine, quinine, and strychnine.     

Robust efficiency and actuator saturation explain healthy heart rate control and variability

The correlation of healthy states with heart rate variability (HRV) using time series analyses is well documented. Whereas these studies note the accepted proximal role of autonomic nervous system balance in HRV patterns, the responsible deeper physiological, clinically relevant mechanisms have not been fully explained. Using mathematical tools from control theory, we combine mechanistic models of basic physiology with experimental exercise data from healthy human subjects to explain causal relationships among states of stress vs. health, HR control, and HRV, and more importantly, the physiologic requirements and constraints underlying these relationships. Nonlinear dynamics play an important explanatory role––most fundamentally in the actuator saturations arising from unavoidable tradeoffs in robust homeostasis and metabolic efficiency. These results are grounded in domain-specific mechanisms, tradeoffs, and constraints, but they also illustrate important, universal properties of complex systems. We show that the study of complex biological phenomena like HRV requires a framework which facilitates inclusion of diverse domain specifics (e.g., due to physiology, evolution, and measurement technology) in addition to general theories of efficiency, robustness, feedback, dynamics, and supporting mathematical tools.Biological systems display a variety of well-known rhythms in physiological signals (1–6), with particular patterns of variability associated with a healthy state (2–6). Decades of research demonstrate that heart rate (HR) in healthy humans has high variability, and loss of this high HR variability (HRV) is correlated with adverse states such as stress, fatigue, physiologic senescence, or disease (6–13). The dominant approach to analysis of HRV has been to focus on statistics and patterns in HR time series that have been interpreted as fractal, chaotic, scale-free, critical, etc. (6–17). The appeal of time series analysis is understandable as it puts HRV in the context of a broad and popular approach to complex systems (5, 18), all while requiring minimal attention to domain-specific (e.g., physiological) details. However, despite intense research activity in this area, there is limited consensus regarding causation or mechanism and minimal clinical application of the observed phenomena (10). This paper takes a completely different approach, aiming for more fundamental rigor (19–24) and methods that have the potential for clinical relevance. Here we use and model data from experimental studies of exercising healthy athletes, to add simple physiological explanations for the largest source of HRV and its changes during exercise. We also present methods that can be used to systematically pursue further explanations about HRV that can generalize to less healthy subjects.Fig. 1 shows the type of HR data analyzed, collected from healthy young athletes (n = 5). The data display responses to changes in muscle work rate on a stationary bicycle during mostly aerobic exercise. Fig. 1A shows three separate exercise sessions with identical workload fluctuations about three different means. With proper sleep, hydration, nutrition, and prevention from overheating, trained athletes can maintain the highest workload in Fig. 1 for hours and the lower and middle levels almost indefinitely. This ability requires robust efficiency: High workloads are sustained while robustly maintaining metabolic homeostasis, a particularly challenging goal in the case of the relatively large, metabolically demanding, and fragile human brain.Open in a separate windowFig. 1.HR responses to simple changes in muscle work rate on a stationary bicycle: Each experimental subject performed separate stationary cycle exercises of ∼10 min for each workload profile, with different means but nearly identical square wave fluctuations around the mean. A typical result is shown from subject 1 for three workload profiles with time on the horizontal axis (zoomed in to focus on a 6-min window). (A) HR (red) and workload (blue); linear local piecewise static fits (black) with different parameters for each exercise. The workload units (most strenuous exercise on top of graph) are shifted and scaled so that the blue curves are also the best global linear fit. (B) Corresponding dynamics fits, either local piecewise linear (black) or global linear (blue). Note that, on all time scales, mean HR increases and variability (HRV) goes down with the increasing workload. Breathing was spontaneous (not controlled).Whereas mean HR in Fig. 1A increases monotonically with workloads, both slow and fast fluctuations (i.e., HRV) in HR are saturating nonlinear functions of workloads, meaning that both high- and low-frequency HRV component goes down. Results from all subjects showed qualitatively similar nonlinearities (SI Appendix). We will argue that this saturating nonlinearity is the simplest and most fundamental example of change in HRV in response to stressors (11, 12, 25) [exercise in the experimental case, but in general also fatigue, dehydration, trauma, infection, even fear and anxiety (6–9, 11, 12, 25)].Physiologists have correlated HRV and autonomic tone (7, 11, 12, 14), and the (im)balance between sympathetic stimulation and parasympathetic withdrawal (12, 26–28). The alternation in autonomic control of HR (more sympathetic and less parasympathetic tone during exercise) serves as an obvious proximate cause for how the HRV changes as shown in Fig. 1, but the ultimate question remains as to why the system is implemented this way. It could be an evolutionary accident, or could follow from hard physiologic tradeoff requirements on cardiovascular control, as work in other systems suggests (1). Here, the explanation of HRV similarly involves hard physiological tradeoffs in robust efficiency and employs the mathematical tools necessary to make this explanation rigorous in the context of large measurement and modeling uncertainties.     

Role of protein dynamics in ion selectivity and allosteric coupling in the NaK channel

Flux-dependent inactivation that arises from functional coupling between the inner gate and the selectivity filter is widespread in ion channels. The structural basis of this coupling has only been well characterized in KcsA. Here we present NMR data demonstrating structural and dynamic coupling between the selectivity filter and intracellular constriction point in the bacterial nonselective cation channel, NaK. This transmembrane allosteric communication must be structurally different from KcsA because the NaK selectivity filter does not collapse under low-cation conditions. Comparison of NMR spectra of the nonselective NaK and potassium-selective NaK2K indicates that the number of ion binding sites in the selectivity filter shifts the equilibrium distribution of structural states throughout the channel. This finding was unexpected given the nearly identical crystal structure of NaK and NaK2K outside the immediate vicinity of the selectivity filter. Our results highlight the tight structural and dynamic coupling between the selectivity filter and the channel scaffold, which has significant implications for channel function. NaK offers a distinct model to study the physiologically essential connection between ion conduction and channel gating.Ion conduction through the pore domain of cation channels is regulated by two gates: an inner gate at the bundle crossing of the pore-lining transmembrane helices and an outer gate located at the selectivity filter (Fig. 1 B and C). These two gates are functionally coupled as demonstrated by C-type inactivation, in which channel opening triggers loss of conduction at the selectivity filter (1–4). A structural model for C-type inactivation has been developed for KcsA, with selectivity filter collapse occurring upon channel opening (4–10). In the reverse pathway, inactivation of the selectivity filter has been linked to changes at the inner gate (5–14). However, flux-dependent inactivation occurs in Na⁺ and Ca²⁺ channels as well and would likely require a structurally different mechanism to explain coupling between the selectivity filter and inner gate (7, 13–18).Open in a separate windowFig. 1.Crystal structures of the nonselective cation channel NaK and the potassium-selective NaK2K mutant show structural changes restricted to the area of the selectivity filter. Alignment of the WT NaK (gray; PDB 3E8H) and NaK2K (light blue; PDB 3OUF) selectivity filters shows a KcsA-like four-ion-binding-site selectivity filter is created by the NaK2K mutations (D66Y and N68D) (A), but no structural changes occur outside the vicinity of the selectivity filter (B). (C) Full-length NaK (green; PDB 2AHZ) represents a closed conformation. Alignment of this structure with NaK (gray) highlights the changes in the M2 hinge (arrow), hydrophobic cluster (residues F24, F28, and F94 shown as sticks), and constriction point (arrow; residue Q103 shown as sticks) upon channel opening. Two (A) or three monomers (B and C) from the tetramer are shown for clarity.This study provides experimental evidence of structural and dynamic coupling between the inner gate and selectivity filter in the NaK channel, a nonselective cation channel from Bacillus cereus (19). These results were entirely unexpected given the available high-resolution crystal structures (20, 21). The NaK channel has the same basic pore architecture as K⁺ channels (Fig. 1 B and C) and has become a second model system for investigating ion selectivity and gating due to its distinct selectivity filter sequence (₆₃TVGDGN₆₈) and structure (19–23). Most strikingly, there are only two ion binding sites in the selectivity filter of the nonselective NaK channel (Fig. 1A) (21, 24). However, mutation of two residues in the selectivity filter sequence converts the NaK selectivity filter to the canonical KcsA sequence (₆₃TVGYGD₆₈; Fig. 1 A and B), leading to K⁺ selectivity and a KcsA-like selectivity filter structure with four ion binding sites (21, 23). This K⁺-selective mutant of NaK is called NaK2K. Outside of the immediate vicinity of the two mutations in the selectivity filter, high-resolution crystal structures of NaK and NaK2K are essentially identical (Fig. 1B) with an all-atom rmsd of only 0.24 Å.NaK offers a distinct model to study the physiologically essential connection between ion conduction and channel gating because there is no evidence for any collapse or structural change in the selectivity filter. The NaK selectivity filter structure is identical in Na⁺ or K⁺ (22) and even in low-ion conditions (25), consistent with its nonselective behavior. Even the selective NaK2K filter appears structurally stable in all available crystal structures (25). Here we use NMR spectroscopy to study bicelle-solubilized NaK. Surprisingly, we find significant differences in the NMR spectra of NaK and NaK2K that extend throughout the protein and are not localized to the selectivity filter region. This, combined with NMR dynamics studies of NaK, suggests a dynamic pathway for transmembrane coupling between the inner gate and selectivity filter of NaK.     

Single-molecule analysis reveals widespread structural variation in multiple myeloma

Multiple myeloma (MM), a malignancy of plasma cells, is characterized by widespread genomic heterogeneity and, consequently, differences in disease progression and drug response. Although recent large-scale sequencing studies have greatly improved our understanding of MM genomes, our knowledge about genomic structural variation in MM is attenuated due to the limitations of commonly used sequencing approaches. In this study, we present the application of optical mapping, a single-molecule, whole-genome analysis system, to discover new structural variants in a primary MM genome. Through our analysis, we have identified and characterized widespread structural variation in this tumor genome. Additionally, we describe our efforts toward comprehensive characterization of genome structure and variation by integrating our findings from optical mapping with those from DNA sequencing-based genomic analysis. Finally, by studying this MM genome at two time points during tumor progression, we have demonstrated an increase in mutational burden with tumor progression at all length scales of variation.Multiple myeloma (MM) is the malignancy of B lymphocytes that terminally differentiate into long-lived, antibody-producing plasma cells. Like other cancers, it is characterized by many genomic aberrations, including single nucleotide variants (SNVs) (1, 2), translocations (most notably involving the Ig heavy chain locus on chr14), and copy number changes, including aneuploidy (3). Recent large-scale sequencing studies have described widespread inter- and intra-tumor genomic heterogeneity (1, 2), clonal evolution (4, 5) and clonal tides (4) in MM. However, most of this work focuses on point mutations and large-scale copy number changes. Although the role of structural variation in normal human genome polymorphism (6, 7) and diseases (8) is widely appreciated, a comprehensive analysis of structural variation in MM is yet to be reported.The therapeutic landscape for MM over the past decade has been transformed with the introduction of proteasome inhibitors (bortezomib, carfilzomib) and thalidomide analogs (9, 10). Consequently, patient survival rates have vastly improved (11). However, MM remains an incurable cancer, and almost all patients with symptomatic MM die of their disease because acquired drug resistance limits the efficacy of current therapies and shortens overall survival (12). Therefore, understanding the impact of contemporary treatments on MM genomic selection may provide fundamental insights for preventing and/or circumventing drug resistance through judicious use of existing therapies and/or rational design of novel agents.To address these issues, we have used optical mapping (7, 13–19) and DNA sequencing to comprehensively characterize structural variation in a primary MM genome at two stages of tumor progression and drug response. The two stages represent a sensitive relapse (MM-S; patient responded to subsequent treatments) and a subsequent refractory relapse (MM-R; no response to any treatments) (SI Materials and Methods and Fig. 1). Optical mapping is a single-molecule system that constructs large datasets comprising ordered restriction maps (Rmaps; 1 Rmap is a restriction map of a single DNA molecule) from individual genomic DNA molecules (Fig. S1). These datasets are submitted to a computational pipeline powered by cluster computing for genome assembly (15) and discovery of structural variants (7, 14, 16, 19). The final assembly presents a relatively unbiased, long-range view of the genome, free of amplification and cloning artifacts, which supports the identification of structural variants and large-scale copy number changes. Previously, optical mapping has been used to uncover structural variation in normal (7), disease risk (17), and cancerous (18) human genomes. Here, we connect long-range structural variation findings from optical mapping with results from whole genome DNA sequencing data analysis (Fig. 1). Such analysis has enabled us to comprehensively identify somatic variation in these tumor samples across all length scales, including structural, copy number, and single nucleotide variation. Additionally, by analyzing these tumor samples at two time points during tumor progression, we have highlighted an increase in mutational burden with tumor progression.Open in a separate windowFig. 1.Overview of cancer genome analysis pipeline comprising optical mapping and DNA sequencing data. Red text indicates that the method identifies somatic variation directly by comparing the tumor to the normal sample. Colored outlines highlight different variation types analyzed by integrating data from both approaches; for example, deletions from optical mapping (blue outline) were analyzed along with deletions from BreakDancer, Pindel, and CNVnator.     

A family of starch-active polysaccharide monooxygenases

The recently discovered fungal and bacterial polysaccharide monooxygenases (PMOs) are capable of oxidatively cleaving chitin, cellulose, and hemicelluloses that contain β(1→4) linkages between glucose or substituted glucose units. They are also known collectively as lytic PMOs, or LPMOs, and individually as AA9 (formerly GH61), AA10 (formerly CBM33), and AA11 enzymes. PMOs share several conserved features, including a monocopper center coordinated by a bidentate N-terminal histidine residue and another histidine ligand. A bioinformatic analysis using these conserved features suggested several potential new PMO families in the fungus Neurospora crassa that are likely to be active on novel substrates. Herein, we report on NCU08746 that contains a C-terminal starch-binding domain and an N-terminal domain of previously unknown function. Biochemical studies showed that NCU08746 requires copper, oxygen, and a source of electrons to oxidize the C1 position of glycosidic bonds in starch substrates, but not in cellulose or chitin. Starch contains α(1→4) and α(1→6) linkages and exhibits higher order structures compared with chitin and cellulose. Cellobiose dehydrogenase, the biological redox partner of cellulose-active PMOs, can serve as the electron donor for NCU08746. NCU08746 contains one copper atom per protein molecule, which is likely coordinated by two histidine ligands as shown by X-ray absorption spectroscopy and sequence analysis. Results indicate that NCU08746 and homologs are starch-active PMOs, supporting the existence of a PMO superfamily with a much broader range of substrates. Starch-active PMOs provide an expanded perspective on studies of starch metabolism and may have potential in the food and starch-based biofuel industries.Polysaccharide monooxygenases (PMOs) are enzymes secreted by a variety of fungal and bacterial species (1–5). They have recently been found to oxidatively degrade chitin (6–8) and cellulose (8–14). PMOs have been shown to oxidize either the C1 or C4 atom of the β(1→4) glycosidic bond on the surface of chitin (6, 7) or cellulose (10–12, 14), resulting in the cleavage of this bond and the creation of new chain ends that can be subsequently processed by hydrolytic chitinases and cellulases. Several fungal PMOs were shown to significantly enhance the degradation of cellulose by hydrolytic cellulases (9), indicating that these enzymes can be used in the conversion of plant biomass into biofuels and other renewable chemicals.There are three families of PMOs characterized thus far: fungal PMOs that oxidize cellulose (9–12) (also known as GH61 and AA9); bacterial PMOs that are active either on chitin (6, 8) or cellulose (8, 13) (also known as CBM33 and AA10); and fungal PMOs that oxidize chitin (AA11) (7). Sequence homology between these three families is very low. Nevertheless, the available structures of PMOs from all three families reveal a conserved fold, including an antiparallel β-sandwich core and a highly conserved monocopper active site on a flat protein surface (Fig. 1A) (2, 6, 7, 9, 10, 15–17). Two histidine residues in a motif termed the histidine brace coordinate the copper center. The N-terminal histidine ligand binds in a bidentate mode, and its imidazole ring is methylated at the N_ε position in fungal PMOs (Fig. 1A).Open in a separate windowFig. 1.(A) Representative overall and active site structures of fungal PMOs (PDB ID code 2YET) (10). (B) Structure of cellulose (18, 19). Chitin also contains β(1→4) linkages and has similar crystalline higher order structure to cellulose. (C) Model structure of amylopectin (23–25). Hydrogen bonds are shown with green dashed lines.Considering the conserved structural features, it is not surprising that the currently known PMOs act on substrates with similar structures. Cellulose and chitin contain long linear chains of β(1→4) linked glucose units and N-acetylglucosamine units, respectively (Fig. 1B). The polymer chains form extensive hydrogen bonding networks, which result in insoluble and very stable crystalline structures (18–21). PMOs are thought to bind to the substrate with their flat active site surface, which orients the copper center for selective oxidation at the C1 or C4 position (6, 16, 22). Some bacterial chitin-binding proteins are cellulose-active PMOs (8, 13, 14), further suggesting that the set of PMO substrates is restricted to β(1→4) linked polymers of glucose and glucose derivatives.Here, we report on the identification of new families of PMOs that contain several key features of previously characterized PMOs, but act on substrates different from cellulose or chitin. A member of one of these novel families of PMOs, NCU08746, was shown to oxidatively cleave amylose, amylopectin, and starch. We designate the NCU08746 family as starch-active PMOs. Both amylose and amylopectin contain linear chains of α(1→4) linked glucose, whereas the latter also contains α(1→6) glycosidic linkages at branch points in the otherwise α(1→4) linked polymer. Unlike cellulose and chitin, amylose and amylopectin do not form microcrystals; instead, they exist in disordered, single helical, and double helical forms (23–27) (see Fig. 1C for example). Starch exists partially in nanocrystalline form, but lacks the flat molecular surfaces as those found in chitin and cellulose. The discovery of starch-active PMOs shows that this oxidative mechanism of glycosidic bond cleavage is more widespread than initially expected.     

Designing DNA-grafted particles that self-assemble into desired crystalline structures using the genetic algorithm

In conventional research, colloidal particles grafted with single-stranded DNA are allowed to self-assemble, and then the resulting crystal structures are determined. Although this Edisonian approach is useful for a posteriori understanding of the factors governing assembly, it does not allow one to a priori design ssDNA-grafted colloids that will assemble into desired structures. Here we address precisely this design issue, and present an experimentally validated evolutionary optimization methodology that is not only able to reproduce the original phase diagram detailing regions of known crystals, but is also able to elucidate several previously unobserved structures. Although experimental validation of these structures requires further work, our early success encourages us to propose that this genetic algorithm–based methodology is a promising and rational materials-design paradigm with broad potential applications.A topic of much interest in the current literature is the self-assembly of colloid particles multiply grafted with ssDNA molecules (1–10). The typical experimental system consists of two types of colloids grafted with complementary ssDNA sequences. Upon cooling, hybridization of the DNA occurs, cross-linking the colloids. Under the right conditions this cross-linking can facilitate the ordering of the colloids into crystal structures. The typical dimensions of colloids result in periodicities comparable to the wavelength of visible length, which have made them attractive for various emergent technologies, e.g., photonic bandgap materials. Classes of plasmonic, light-emitting, and catalytic metamaterials can be realized via the self-assembly of ssDNA-grafted colloids into specified 3D arrays.Although much work has examined the effects of temperature, DNA length, linker DNA groups, size of colloids, etc., on structure formation, it has been largely empirically driven. However, there has been some progress in theory and simulation on understanding this assembly process (5, 6, 11–13). The recent work of Starr and coworkers, for example, has emphasized the complicated phase and assembly behavior of these materials (11, 12, 14). Travesset and coworkers (5) and Olvera de la Cruz and coworkers (15) have used large-scale molecular dynamics simulations to study equilibrium aspects and the kinetics of self-assembly, including kinetic traps like gel formation. Crocker and coworker developed a quantitative model based on experimental studies to predict ssDNA-induced particle interactions, the driving force for self-assembly (16). Similarly, Frenkel and coworkers has also defined a general accurate theory of valence-limited colloidal interactions (17). In a similar vein, Mirkin and coworkers proposed a rule-based complementary contact model (CCM) to predict the formation of crystal structures by ssDNA-grafted colloids (7). This model was used to explain the four crystal structures experimentally observed.Although the controlled spatial organization of colloidal particles is thus a topic of broad interest, most current work has taken the forward modeling approach: i.e., one starts with a pair of ssDNA colloids with known structures (or product formulation, Fig. 1) and then uses theory and/or simulation to examine the superstructure it assembles into. These predictions are validated against experiments as a means of calibrating the fidelity of the models and the modeling tools. Here we focus on the reverse problem (Fig. 1), where we design ssDNA-grafted colloids that can assemble into desired superstructures.Open in a separate windowFig. 1.Comparison of conventional and proposed paradigms.     

Single-molecule spectroscopy reveals how calmodulin activates NO synthase by controlling its conformational fluctuation dynamics

Mechanisms that regulate the nitric oxide synthase enzymes (NOS) are of interest in biology and medicine. Although NOS catalysis relies on domain motions, and is activated by calmodulin binding, the relationships are unclear. We used single-molecule fluorescence resonance energy transfer (FRET) spectroscopy to elucidate the conformational states distribution and associated conformational fluctuation dynamics of the two electron transfer domains in a FRET dye-labeled neuronal NOS reductase domain, and to understand how calmodulin affects the dynamics to regulate catalysis. We found that calmodulin alters NOS conformational behaviors in several ways: It changes the distance distribution between the NOS domains, shortens the lifetimes of the individual conformational states, and instills conformational discipline by greatly narrowing the distributions of the conformational states and fluctuation rates. This information was specifically obtainable only by single-molecule spectroscopic measurements, and reveals how calmodulin promotes catalysis by shaping the physical and temporal conformational behaviors of NOS.Although proteins adopt structures determined by their amino acid sequences, they are not static objects and fluctuate among ensembles of conformations (1). Transitions between these states can occur on a variety of length scales (Å to nm) and time scales (ps to s) and have been linked to functionally relevant phenomena such as allosteric signaling, enzyme catalysis, and protein–protein interactions (2–4). Indeed, protein conformational fluctuations and dynamics, often associated with static and dynamic inhomogeneity, are thought to play a crucial role in biomolecular functions (5–11). It is difficult to characterize such spatially and temporally inhomogeneous dynamics in bulk solution by an ensemble-averaged measurement, especially in proteins that undergo multiple-conformation transformations. In such cases, single-molecule spectroscopy is a powerful approach to analyze protein conformational states and dynamics under physiological conditions, and can provide a molecular-level perspective on how a protein’s structural dynamics link to its functional mechanisms (12–21).A case in point is the nitric oxide synthase (NOS) enzymes (22–24), whose nitric oxide (NO) biosynthesis involves electron transfer reactions that are associated with relatively large-scale movement (tens of Å) of the enzyme domains (Fig. 1A). During catalysis, NADPH-derived electrons first transfer into an FAD domain and an FMN domain in NOS that together comprise the NOS reductase domain (NOSr), and then transfer from the FMN domain to a heme group that is bound in a separate attached “oxygenase” domain, which then enables NO synthesis to begin (22, 25–27). The electron transfers into and out of the FMN domain are the key steps for catalysis, and they appear to rely on the FMN domain cycling between electron-accepting and electron-donating conformational states (28, 29) (Fig. 1B). In this model, the FMN domain is suggested to be highly dynamic and flexible due to a connecting hinge that allows it to alternate between its electron-accepting (FAD→FMN) or closed conformation and electron-donating (FMN→heme) or open conformation (Fig. 1 A and B) (28, 30–36). In the electron-accepting closed conformation, the FMN domain interacts with the NADPH/FAD domain (FNR domain) to receive electrons, whereas in the electron donating open conformation the FMN domain has moved away to expose the bound FMN cofactor so that it may transfer electrons to a protein acceptor like the NOS oxygenase domain, or to a generic protein acceptor like cytochrome c. In this way, the reductase domain structure cycles between closed and open conformations to deliver electrons, according to a conformational equilibrium that determines the movements and thus the electron flux capacity of the FMN domain (25, 28, 32, 34, 35, 37). A similar conformational switching mechanism is thought to enable electron transfer through the FMN domain in the related flavoproteins NADPH-cytochrome P450 reductase and methionine synthase reductase (38–42).Open in a separate windowFig. 1.(A) The nNOSr ribbon structure (from PDB: 1TLL) showing bound FAD (yellow) in FNR domain (green), FMN (orange) in FMN domain (yellow), connecting hinge (blue), and the Cy3–Cy5 label positions (pink) and distance (42 Å, dashed line). (B) Cartoon of an equilibrium between the FMN-closed and FMN-open states, with Cy dye label positions indicated. (C) Cytochrome c reductase activity of nNOSr proteins in their CaM-bound and CaM-free states. Color scheme of bar graphs: Black, WT nNOSr unlabeled; Red, Cys-lite (CL) nNOSr unlabeled; Blue, E827C/Q1268C CL nNOSr unlabeled; and Dark cyan, E827C/Q1268C CL nNOSr labeled.NOS enzymes also contain a calmodulin (CaM) binding domain that is located just before the N terminus of the FMN domain (Fig. 1B), and this provides an important layer of regulation (25, 27). CaM binding to NOS enzymes increases electron transfer from NADPH through the reductase domain and also triggers electron transfer from the FMN domain to the NOS heme as is required for NO synthesis (31, 32). The ability of CaM, or similar signaling proteins, to regulate electron transfer reactions in enzymes is unusual, and the mechanism is a topic of interest and intensive study. It has long been known that CaM binding alters NOSr structure such that, on average, it populates a more open conformation (43, 44). Recent equilibrium studies have detected a buildup of between two to four discreet conformational populations in NOS enzymes and in related flavoproteins, and in some cases, have also estimated the distances between the bound FAD and FMN cofactors in the different species (26, 36, 37, 39, 40), and furthermore, have confirmed that CaM shifts the NOS population distribution toward more open conformations (34, 36, 45). Although valuable, such ensemble-averaged results about conformational states cannot explain how electrons transfer through these enzymes, or how CaM increases the electron flux in NOS, because answering these questions requires a coordinate understanding of the dynamics of the conformational fluctuations. Indeed, computer modeling has indicated that a shift toward more open conformations as is induced by CaM binding to nNOS should, on its own, actually diminish electron flux through nNOS and through certain related flavoproteins (38). Despite its importance, measuring enzyme conformational fluctuation dynamics is highly challenging, and as far as we know, there have been no direct measures on the NOS enzymes or on related flavoproteins, nor studies on how CaM binding might influence the conformational fluctuation dynamics in NOS.To address this gap, we used single-molecule fluorescence energy resonance transfer (FRET) spectroscopy to characterize individual molecules of nNOSr that had been labeled at two specific positions with Cyanine 3 (Cy3) donor and Cyanine 5 (Cy5) acceptor dye molecules, regarding their conformational states distribution and the associated conformational fluctuation dynamics, which in turn enabled us to determine how CaM binding impacts both parameters. This work provides a unique perspective and a novel study of the NOS enzymes and within the broader flavoprotein family, which includes the mammalian enzymes methionine synthase reductase (MSR) and cytochrome P450 reductase (CPR), and reveals how CaM’s control of the conformational behaviors may regulate the electron transfer reactions of NOS catalysis.     

Tuning a riboswitch response through structural extension of a pseudoknot

Structural and dynamic features of RNA folding landscapes represent critical aspects of RNA function in the cell and are particularly central to riboswitch-mediated control of gene expression. Here, using single-molecule fluorescence energy transfer imaging, we explore the folding dynamics of the preQ₁ class II riboswitch, an upstream mRNA element that regulates downstream encoded modification enzymes of queuosine biosynthesis. For reasons that are not presently understood, the classical pseudoknot fold of this system harbors an extra stem–loop structure within its 3′-terminal region immediately upstream of the Shine–Dalgarno sequence that contributes to formation of the ligand-bound state. By imaging ligand-dependent preQ₁ riboswitch folding from multiple structural perspectives, we reveal that the extra stem–loop strongly influences pseudoknot dynamics in a manner that decreases its propensity to spontaneously fold and increases its responsiveness to ligand binding. We conclude that the extra stem–loop sensitizes this RNA to broaden the dynamic range of the ON/OFF regulatory switch.A variety of small metabolites have been found to regulate gene expression in bacteria, fungi, and plants via direct interactions with distinct mRNA folds (1–4). In this form of regulation, the target mRNA typically undergoes a structural change in response to metabolite binding (5–9). These mRNA elements have thus been termed “riboswitches” and generally include both a metabolite-sensitive aptamer subdomain and an expression platform. For riboswitches that regulate the process of translation, the expression platform minimally consists of a ribosomal recognition site [Shine–Dalgarno (SD)]. In the simplest form, the SD sequence overlaps with the metabolite-sensitive aptamer domain at its downstream end. Representative examples include the S-adenosylmethionine class II (SAM-II) (10) and the S-adenosylhomocysteine (SAH) riboswitches (11, 12), as well as prequeuosine class I (preQ₁-I) and II (preQ₁-II) riboswitches (13, 14). The secondary structures of these four short RNA families contain a pseudoknot fold that is central to their gene regulation capacity. Although the SAM-II and preQ₁-I riboswitches fold into classical pseudoknots (15, 16), the conformations of the SAH (17) and preQ₁-II counterparts are more complex and include a structural extension that contributes to the pseudoknot architecture (14). Importantly, the impact and evolutionary significance of these “extra” stem–loop elements on the function of the SAH and preQ₁-II riboswitches remain unclear.PreQ₁ riboswitches interact with the bacterial metabolite 7-aminomethyl-7-deazaguanine (preQ₁), a precursor molecule in the biosynthetic pathway of queuosine, a modified base encountered at the wobble position of some transfer RNAs (14). The general biological significance of studying the preQ₁-II system stems from the fact that this gene-regulatory element is found almost exclusively in the Streptococcaceae bacterial family. Moreover, the preQ₁ metabolite is not generated in humans and has to be acquired from the environment (14). Correspondingly, the preQ₁-II riboswitch represents a putative target for antibiotic intervention. Although preQ₁ class I (preQ₁-I) riboswitches have been extensively investigated (18–28), preQ₁ class II (preQ₁-II) riboswitches have been largely overlooked despite the fact that a different mode of ligand binding has been postulated (14).The consensus sequence and the secondary structure model for the preQ₁-II motif (COG4708 RNA) (Fig. 1A) comprise ∼80–100 nt (14). The minimal Streptococcus pneumoniae R6 aptamer domain sequence binds preQ₁ with submicromolar affinity and consists of an RNA segment forming two stem–loops, P2 and P4, and a pseudoknot P3 (Fig. 1B). In-line probing studies suggest that the putative SD box (AGGAGA; Fig. 1) is sequestered by pseudoknot formation, which results in translational-dependent gene regulation of the downstream gene (14).Open in a separate windowFig. 1.PreQ₁ class II riboswitch. (A) Chemical structure of 7-aminomethyl-7-deazaguanosine (preQ₁); consensus sequence and secondary structure model for the COG4708 RNA motif (adapted from reference 14). Nucleoside presence and identity as indicated. (B) S. pneumoniae R6 preQ₁-II RNA aptamer investigated in this study. (C) Schematics of an H-type pseudoknot with generally used nomenclature for comparison.Here, we investigated folding and ligand recognition of the S. pneumoniae R6 preQ₁-II riboswitch, using complementary chemical, biochemical, and biophysical methods including selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE), mutational analysis experiments, 2-aminopurine fluorescence, and single-molecule fluorescence resonance energy transfer (smFRET) imaging. In so doing, we explored the structural and functional impact of the additional stem–loop element in the context of its otherwise “classical” H-type pseudoknot fold (29–32) (Fig. 1C). Our results reveal that the unique 3′-stem–loop element in the preQ₁-II riboswitch contributes to the process of SD sequestration, and thus the regulation of gene expression, by modulating both its intrinsic dynamics and its responsiveness to ligand binding.     

Structural and functional analysis of two di-domain aromatase/cyclases from type II polyketide synthases

Aromatic polyketides make up a large class of natural products with diverse bioactivity. During biosynthesis, linear poly-β-ketone intermediates are regiospecifically cyclized, yielding molecules with defined cyclization patterns that are crucial for polyketide bioactivity. The aromatase/cyclases (ARO/CYCs) are responsible for regiospecific cyclization of bacterial polyketides. The two most common cyclization patterns are C7–C12 and C9–C14 cyclizations. We have previously characterized three monodomain ARO/CYCs: ZhuI, TcmN, and WhiE. The last remaining uncharacterized class of ARO/CYCs is the di-domain ARO/CYCs, which catalyze C7–C12 cyclization and/or aromatization. Di-domain ARO/CYCs can further be separated into two subclasses: “nonreducing” ARO/CYCs, which act on nonreduced poly-β-ketones, and “reducing” ARO/CYCs, which act on cyclized C9 reduced poly-β-ketones. For years, the functional role of each domain in cyclization and aromatization for di-domain ARO/CYCs has remained a mystery. Here we present what is to our knowledge the first structural and functional analysis, along with an in-depth comparison, of the nonreducing (StfQ) and reducing (BexL) di-domain ARO/CYCs. This work completes the structural and functional characterization of mono- and di-domain ARO/CYCs in bacterial type II polyketide synthases and lays the groundwork for engineered biosynthesis of new bioactive polyketides.The biosynthesis of type II aromatic polyketide natural products has been extensively investigated because of the versatile pharmacological properties of these compounds (1–7). The type II polyketide synthase (PKS) is composed of dissociated enzymes that are used iteratively and are responsible for the elongation, cyclization, and modification of the polyketide chain (Fig. 1) (3, 4, 8, 9). The regiospecific cyclization of an acyl carrier protein (ACP)-linked linear poly-β-ketone intermediate is a key transformation catalyzed by type II PKSs. However, the enzymatic mechanism of cyclization remains poorly understood (10–14). Without such knowledge, the polyketide cyclization pattern cannot be predicted; a full understanding of this process at the molecular level is essential for future biosynthetic engineering efforts.Open in a separate windowFig. 1.Schematic diagram of ARO/CYC activity and cyclization specificity in representative type II PKSs. The monodomain ARO/CYCs TcmN (PDB ID 2RER) and WhiE (PDB ID 3TVR) act on unreduced polyketide intermediates to generate C9–C14 cyclized and aromatized products. The monodomain ARO/CYC ZhuI (PDB ID 3TFZ) and di-domain ARO/CYC StfQ act on unreduced polyketide intermediates to generate C7–C12 cyclized and aromatized products. The di-domain ARO/CYC BexL acts on C9 reduced, C7–C12 cyclized intermediates and catalyzes the aromatization of the C7–12 cyclized ring by dehydration of the C9 hydroxyl group.In 2008, we reported the crystal structure of the first aromatase/cyclase (ARO/CYC) (TcmN ARO/CYC), which is a single-domain protein (15). On the basis of the structural analysis and mutagenesis results, we proposed that monodomain ARO/CYCs contain an active site and are capable of catalyzing polyketide cyclization and aromatization. Since then, we have performed structural and biochemical studies of two other monodomain ARO/CYCs: WhiE and ZhuI (Fig. 1) (16, 17). These studies provided strong evidence supporting our hypothesis that ARO/CYC is the site of polyketide cyclization. However, many type II PKSs contain di-domain ARO/CYCs that have two seemingly identical domains (18–23). Why these enzymes require two domains (as opposed to just one) and how they conduct the cyclization/aromatization are not understood.The di-domain ARO/CYCs are found in both nonreducing and reducing PKSs (18, 24). In nonreducing systems, the di-domain ARO/CYCs regiospecifically cyclize a polyketide between C7 and C12, followed by aromatization (18). In reducing systems, a ketoreductase (KR) first regiospecifically cyclizes the linear poly-β-ketone from C12 to C7, followed by a highly specific C9-carbonyl reduction (7, 25). A di-domain ARO/CYC then catalyzes the dehydration of the C9 hydroxyl, followed by first-ring aromatization (Fig. 1) (14). Therefore, in a nonreducing system, the growing poly-β-ketone intermediate is transported directly from the ketosynthase (KS) to the ARO/CYC. In contrast, in a reducing system, the intermediate needs to be transported from KS to KR and then to ARO/CYC. Before this study, there was no knowledge of whether there is any difference between the di-domain ARO/CYCs in reducing versus nonreducing PKSs, nor any information on the role that ARO/CYCs may play in determining the product specificity of reducing and nonreducing PKSs. The key issue that has hampered the investigation of this group of enzymes is the difficulty in protein crystallization.To critically compare the reducing and nonreducing di-domain ARO/CYCs, we have chosen StfQ as a model nonreducing di-domain ARO/CYC and BexL as a model reducing di-domain ARO/CYC (Fig. 1). StfQ is a di-domain ARO/CYC from Streptomyces steffisburgensis and is part of the nonreducing PKS catalyzing the biosynthesis of steffimycin, which shows promising antitumor activities (26–28). StfQ is the enzyme responsible for the C7–C12 first-ring cyclization and aromatization of the elongated poly-β-ketone substrate. In contrast, BexL is a di-domain ARO/CYC in the reducing PKS responsible for the biosynthesis of the anticancer agent BE-7585A. The linear poly-β-ketone precursor of BE-7585A is first cyclized, then reduced at the C9 position by KR, and then aromatized by BexL (Fig. 1) (24). Both StfQ and BexL use 20-carbon poly-β-ketone substrates; therefore, the structural enzymology of these two ARO/CYCs offers a great opportunity for side-by-side comparison with insight into the catalytic mechanisms of di-domain ARO/CYCs. Here we present the first structural and biochemical characterization, to our knowledge, of two di-domain ARO/CYCs, StfQ and BexL, using X-ray crystallography, structure-based mutagenesis, in silico docking, and in vitro functional assays.     

Human genome–guided identification of memory-modulating drugs

In the last decade there has been an exponential increase in knowledge about the genetic basis of complex human traits, including neuropsychiatric disorders. It is not clear, however, to what extent this knowledge can be used as a starting point for drug identification, one of the central hopes of the human genome project. The aim of the present study was to identify memory-modulating compounds through the use of human genetic information. We performed a multinational collaborative study, which included assessment of aversive memory—a trait central to posttraumatic stress disorder—and a gene-set analysis in healthy individuals. We identified 20 potential drug target genes in two genomewide-corrected gene sets: the neuroactive ligand–receptor interaction and the long-term depression gene set. In a subsequent double-blind, placebo-controlled study in healthy volunteers, we aimed at providing a proof of concept for the genome-guided identification of memory modulating compounds. Pharmacological intervention at the neuroactive ligand–receptor interaction gene set led to significant reduction of aversive memory. The findings demonstrate that genome information, along with appropriate data mining methodology, can be used as a starting point for the identification of memory-modulating compounds.Recent advances in human genetics have led to an unprecedented rate of discovery of genes related to complex human disease, including neuropsychiatric disorders (1–3). The human genome–based gain of knowledge is certainly expected to have a large impact on drug discovery in complex human disease (4–6). It is, however, still not clear to what extent this knowledge can be used as a starting point for the identification of druggable molecular pathways of complex traits (7), including mental disorders (8).Genomewide association studies (GWASs) using single-marker statistics have been very successful in identifying trait-associated single-gene loci (9). It is, however, widely accepted that single marker–based analyses have limited power to identify the genetic basis of a given trait, as for example, many loci will fail to reach stringent genomewide significance threshold, despite the fact that they may be genuinely associated with the trait. Triggered by statistical approaches for the analysis of gene expression, gene set–based analytical methods have recently become available. These methods aim at identifying biologically meaningful sets of genes associated with a certain trait, rather than focusing on a single GWAS gene locus (10). By taking into account prior biological knowledge, gene set–based approaches examine whether test statistics for a group of related genes have consistent deviation from chance (10). As shown recently in studies on autism (11), bipolar disorder (12, 13), attention deficit hyperactivity disorder (ADHD) (14), and schizophrenia (15), such approaches can convincingly identify convergent molecular pathways relevant to neuropsychiatry. Importantly, the identification of groups of functionally related genes is likely to facilitate drug discovery, because the most significant single loci from a GWAS might not be the best candidates for therapeutic intervention (7, 10).In the present study, we focused on emotionally aversive memory—a trait central to anxiety disorders such as posttraumatic stress disorder (PTSD) (16–23). Strong memory for emotionally arousing events can be seen as a primarily adaptive phenomenon, which helps us to remember vital information (e.g., dangerous situations). In case of an extremely aversive event, however, this mechanism can also lead to intrusive and persistent traumatic memories, thereby contributing to the development and symptoms of PTSD (18–22). Symptoms related to aversive memory include intrusive daytime recollections, traumatic nightmares, and flashbacks in which components of the event are relived. Aversive memory is a genetically complex trait as shown both in healthy subjects and in traumatized individuals (17, 23). Furthermore, we recently reported evidence suggesting a genetic link between the predisposition to build strong aversive memories and the risk for PTSD (16).Based on these observations, we developed a process (Fig. 1) aimed at identifying gene sets related to human aversive memory, followed by a pharmacological intervention study as proof-of-concept for the genome-guided identification of memory-modulating drugs.Open in a separate windowFig. 1.Drug discovery process.     

Reaction-based fluorescent sensor for investigating mobile Zn2+ in mitochondria of healthy versus cancerous prostate cells

Chelatable, mobile forms of divalent zinc, Zn(II), play essential signaling roles in mammalian biology. A complex network of zinc import and transport proteins has evolved to control zinc concentration and distribution on a subcellular level. Understanding the action of mobile zinc requires tools that can detect changes in Zn(II) concentrations at discrete cellular locales. We present here a zinc-responsive, reaction-based, targetable probe based on the diacetyled form of Zinpyr-1. The compound, (6-amidoethyl)triphenylphosphonium Zinpyr-1 diacetate (DA-ZP1-TPP), is essentially nonfluorescent in the metal-free state; however, exposure to Zn(II) triggers metal-mediated hydrolysis of the acetyl groups to afford a large, rapid, and zinc-induced fluorescence response. DA-ZP1-TPP is insensitive to intracellular esterases over a 2-h period and is impervious to proton-induced turn-on. A TPP unit is appended for targeting mitochondria, as demonstrated by live cell fluorescence imaging studies. The practical utility of DA-ZP1-TPP is demonstrated by experiments revealing that, in contrast to healthy epithelial prostate cells, tumorigenic cells are unable to accumulate mobile zinc within their mitochondria.Divalent zinc, Zn(II), is a trace nutrient critical for physiological function. Although most biological zinc ions are tightly associated with proteins (1), pools of loosely bound or “mobile” forms (2) serve regulatory or signaling functions (3), including nucleation of protein self-assembly (4), triggering of signaling pathways (5), and modification of cellular metabolism (6). In this capacity, mobile zinc performs essential tasks in the physiology of the central nervous system, pancreas, and prostate (5, 7, 8).Mobile zinc is an indispensable component of prostate physiology. The prostate contains more zinc than any other soft tissue in the body, and there is a clear correlation between total prostatic zinc levels and cancer (8). Despite extensive investigation, however, our molecular understanding of mobile zinc in the prostate remains incomplete (7, 8). This situation is related in part to the complex spatiotemporal mechanisms through which the prostate controls zinc levels. At least three Zrt/Irt-like proteins (ZIPs) and six zinc transport proteins (ZnT) are expressed in a lobe-dependent manner in the prostate (7); for example, the epithelium of the human peripheral lobe accumulates high concentrations of zinc, primarily through a ZIP1-dependent process (9). Inside prostate epithelial cells, Zn(II) accumulates in mitochondria, where it can inhibit aconitase and truncate the citric acid cycle, facilitating cellular buildup of citrate ion (6, 10). Alterations to prostatic zinc trafficking are incontrovertibly linked to the onset and progression of prostate cancer (11–13).Understanding the transport, accumulation, and action of mobile zinc in the prostate and other tissues requires tools that can report on changes in mobile zinc concentration at defined locales within a live cell environment. Zinc-responsive fluorescent reporters are well suited for this purpose. Of the various classes of zinc sensors (14), small molecule fluorescein-based scaffolds are the most broadly implemented (3, 15). Fluorescein is bright (εΦ), nontoxic, and compatible with one- and two-photon microscopy (16). Fluorescein has well-established synthetic pathways and has been fashioned into probes with varying mobile zinc affinities and dynamic ranges (16). A persistent limitation of fluorescein-based sensors is their unpredictability with respect to plasma membrane permeability and subcellular localization. Seemingly small changes in chemical structure can have dramatic effects on sensor permeability and localization (15).The capricious localization of fluorescein-based probes contrasts with protein-based zinc sensors, which offer programmable probe localization (17, 18). Although protein-based (19) and peptide-based (20) targeting strategies have recently been used to direct the localization of fluorescein-based zinc sensors, controlling the subcellular accumulation of such probes remains a significant challenge.To avoid the unpredictability of de novo sensor design, we adopted the aminoethyltriphenylphosphonium (TPP) ion as a small chemical tag to direct a mobile zinc sensor to the mitochondrion, a well-established strategy (21–27) based on known intracellular physiochemical properties. We created a derivative of the widely applied zinc sensor ZP1 (16) with the TPP ion attached via an amide linkage to the 6-position on the benzoic acid ring of the fluorophore (Fig. 1). Unexpectedly, the resulting construct, ZP1-TPP, sequestered within endosomes/lysosomes and lost its ability to respond to changes in mobile zinc concentrations (vide infra).Open in a separate windowFig. 1.Schematic representation of zinc-induced fluorescence from DA-ZP1-TPP. (A) ZP1-TPP is rendered nonfluorescent by addition of acetyl groups on the phenolic oxygen atoms of the xanthene ring. (B) Coordination of Zn(II) enhances fluorescence intensity by promoting ester hydrolysis and alleviating PeT originating from the two DPA arms. (C) Fluorescence enhancement is partially reversed by removing Zn(II), which restores the fluorescence-quenching ability of the DPA groups.To prevent such endosomal localization and afford TPP-mediated mitochondrial targeting in live cells, we altered the physical properties of ZP1-TPP through conversion to the fluorescein diacetate analog. Not only did this conversion result in the desired loss of endosomal/lysosomal entrapment, but the resulting probe, (6-amidoethyl)triphenylphosphonium Zinpyr-1 diacetate (DA-ZP1-TPP), proved to have several additional highly desirable properties. The presence of the acetyl groups provided nearly complete fluorescence quenching that was rapidly reversed on exposure to Zn(II), the Lewis acidity of which mediated hydrolysis of the ester groups (28) to afford a large, rapid, zinc-induced fluorescence response (Fig. 1B). Moreover, DA-ZP1-TPP is insensitive to intracellular esterases over a 2-h period, impervious to proton-induced turn-on, and an excellent probe for targeting mitochondria in live cells. Unlike most reaction-based probes (29, 30), DA-ZP1-TPP also retains a measure of reversibility, owing to photo-induced electron transfer (PeT) from the dipicolylamine (DPA) groups in the apo state of the sensor (Fig. 1C).To demonstrate the practical utility of DA-ZP1-TPP, we conducted live cell imaging studies of three different prostate cell lines. The results of these experiments revealed that, in contrast to healthy epithelial prostate cells, tumorigenic cells are unable to accumulate mobile zinc within their mitochondria.