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.     

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.     

Solid-phase peptide synthesis and solid-phase fragment coupling mediated by isonitriles

The synthesis of polypeptides on solid phase via mediation by isonitriles is described. The acyl donor is a thioacid, which presumably reacts with the isonitrile to generate a thio-formimidate carboxylate mixed anhydride intermediate. Applications of this chemistry to reiterative solid-phase peptide synthesis as well as solid-phase fragment coupling are described.Amide bond formations are arguably among the most important constructions in organic chemistry (1, 2). The centrality of the amide linkage, as found in polypeptides and proteins, in the maintenance of life hardly needs restatement. Numerous strategies, resulting in a vast array of protocols to synthesize biologically active polypeptides and proteins, have been demonstrated (3, 4). Central to reiterative polypeptide bond formations was the discovery and remarkable development of solid-phase peptide synthesis (SPPS) (5, 6). The extraordinary impact of SPPS in fostering enhanced access to homogeneous polypeptides is clear to everyone in the field.As we have described elsewhere, by classical, mechanistic reasoning, we were led to conjecture about some hitherto-unexplored possibilities relevant to the chemistry of isonitriles (7–14). It was anticipated that isonitriles might be able to mediate the acylation of amines, thus giving rise to amides (15). Early experiments focused on free carboxylic acids as the acylating agents. As our studies progressed, it was found that the combination of thioacids, amines, and isonitriles leads to the efficient formation of amide bonds under stoichiometric or near-stoichiometric conditions (7–13, 16, 17). Although there remain unresolved issues of detail and nuance, the governing mechanism for amide formation under these conditions involves reaction of the thioacid, 1, with an isonitrile, 2, to generate a thio-formimidate carboxylate mixed anhydride (thio-FCMA), 3, which is intercepted by the “acyl-accepting” amine to generate amide, 5, and thioformamide, 6 (Fig. 1). The efficiency of the amidation was further improved through the use of hydroxybenzotriazole (HOBt) (18), which could well give rise to HOBt ester 7, although this pathway has not been mechanistically proven.Open in a separate windowFig. 1.Isonitrile-mediated amidation; structure of OT.The potentialities of the isonitrile-mediated amidation method were foreshadowed via its application to the synthesis of cyclosporine (19). The power of the method was particularly well demonstrated in the context of our recent total synthesis of oxytocin (OT) (20), wherein isonitrile mediation was used in each of the peptide bond constructions, leading to the synthesis of the hormone in high yield and excellent purity. This nonapeptide is involved in a range of biological functions including parturition and lactation (21, 22). Signaling of OT to its receptor (OTR) is apparently an important factor in quality maintenance of various CNS functions (23). The ability to synthesize such modestly sized, but bio-impactful peptides in both native (wild-type) form, and as strategically modified variants, is one of the current missions of our laboratory, with the objective of possible applications to the very serious problem of autism (24–26).     

Quantitative dissection of hydrogen bond-mediated proton transfer in the ketosteroid isomerase active site

Hydrogen bond networks are key elements of protein structure and function but have been challenging to study within the complex protein environment. We have carried out in-depth interrogations of the proton transfer equilibrium within a hydrogen bond network formed to bound phenols in the active site of ketosteroid isomerase. We systematically varied the proton affinity of the phenol using differing electron-withdrawing substituents and incorporated site-specific NMR and IR probes to quantitatively map the proton and charge rearrangements within the network that accompany incremental increases in phenol proton affinity. The observed ionization changes were accurately described by a simple equilibrium proton transfer model that strongly suggests the intrinsic proton affinity of one of the Tyr residues in the network, Tyr16, does not remain constant but rather systematically increases due to weakening of the phenol–Tyr16 anion hydrogen bond with increasing phenol proton affinity. Using vibrational Stark spectroscopy, we quantified the electrostatic field changes within the surrounding active site that accompany these rearrangements within the network. We were able to model these changes accurately using continuum electrostatic calculations, suggesting a high degree of conformational restriction within the protein matrix. Our study affords direct insight into the physical and energetic properties of a hydrogen bond network within a protein interior and provides an example of a highly controlled system with minimal conformational rearrangements in which the observed physical changes can be accurately modeled by theoretical calculations.Hydrogen bond networks are ubiquitous structural features within proteins, and they play key roles linking secondary and tertiary structural elements and spanning protein–protein interfaces. Such networks are especially common within enzyme active sites, where they position protein and substrate groups for catalysis, stabilize charge rearrangements during chemical transformations, and mediate proton transfers (1). Despite the prevalence and critical structural and functional roles of hydrogen bond networks, incisive dissection of their physical properties within the idiosyncratic interior of folded proteins remains difficult.Hydrogen-bonded protons are not observed in the vast majority of protein X-ray structures due to the low X-ray scattering power of hydrogen atoms (2). Thus, the presence of hydrogen bond networks is typically inferred from the proximity and orientation of hydrogen bond donor and acceptor groups within refined protein structural models. The inherent inability of most X-ray diffraction studies to monitor proton positions imposes additional challenges for dissecting the physical features that influence the equilibrium protonation states of specific residues along a hydrogen-bonded proton transfer network. Furthermore, it remains extremely challenging to study the electrostatic consequences of charge rearrangements that accompany hydrogen bond-mediated proton transfers. Few experimental methods exist to vary the ionization properties of discrete protein groups incrementally, and structural rearrangements within the protein matrix that typically accompany charge rearrangements complicate computational modeling and the straightforward interpretation of the electrostatic properties of protein active sites and interiors (3–5).Bacterial ketosteroid isomerase (KSI) from Pseudomonas putida KSI (pKSI) and Comamonas testosteroni KSI has been a powerful system with which to study the physical properties of hydrogen bonds within an enzyme active site (6–13). KSI uses a general base, D40 (pKSI numbering), to deprotonate steroid substrates and form a dienolate reaction intermediate that is stabilized by hydrogen bonds donated by Y16 and protonated D103. Y16 is further linked via hydrogen bonds to Y57 and Y32, forming an extended active site hydrogen bond network in pKSI (Fig. 1A). Phenolic ligands, such as single-ring phenols, two-ring naphthols, and four-ring steroids like equilenin or estradiol, can bind in the KSI active site as negatively charged oxyanions and accept hydrogen bonds from Y16 and D103, mimicking the oxyanion charge localization of the dienolate reaction intermediate and dienolate-like transition states (6–8, 14, 15) (Fig. 1B). A homologous series of bound phenols or naphthols bearing different electron-withdrawing substituents provides a deft experimental tool with which to incrementally vary the proton affinity and negative charge density of the phenolic oxygen (16). These changes tune the structure and strength of hydrogen bonds formed to phenolic ligands (17–19), and thus provide a systematic probe of the physical and energetic properties of the hydrogen bond network within the KSI oxyanion hole (6–9, 11, 13) and the response of the surrounding protein matrix to such changes (20, 21).Open in a separate windowFig. 1.KSI reaction and reaction intermediate analog. (A) KSI reaction mechanism for isomerization of 5-androstene-3,17-dione. (B) Schematic depiction of an ionized substituted phenol bound at the KSI D40N active site.Recent studies with the D40N pKSI mutant, which mimics the protonated D40 present in the KSI–dienolate intermediate complex (Fig. 1A), have provided evidence that ligands of increasing pK_a are bound as an increasing population of neutral, protonated phenol (11, 13, 22). These results suggest that an unspecified active site residue can ionize with increasing phenol pK_a, resulting in a net proton transfer to the bound ligand. We have used site-specific NMR and IR probes and KSI semisynthesis to determine that either of two different Tyrs within the extended hydrogen bond network can ionize, and we have systematically mapped the changes in their equilibrium ionization states as a function of the proton affinity and hydrogen bonding capability of the phenolic ligand. We further measured the electric field changes at discrete active site positions due to charge rearrangements within the hydrogen bond network. We demonstrate that a static continuum electrostatic model with a low dielectric can accurately describe these changes, suggesting a high degree of structural organization and the absence of substantial conformational rearrangement in response to charge rearrangement within the active site.     

Detection of genomic variations and DNA polymorphisms and impact on analysis of meiotic recombination and genetic mapping

DNA polymorphisms are important markers in genetic analyses and are increasingly detected by using genome resequencing. However, the presence of repetitive sequences and structural variants can lead to false positives in the identification of polymorphic alleles. Here, we describe an analysis strategy that minimizes false positives in allelic detection and present analyses of recently published resequencing data from Arabidopsis meiotic products and individual humans. Our analysis enables the accurate detection of sequencing errors, small insertions and deletions (indels), and structural variants, including large reciprocal indels and copy number variants, from comparisons between the resequenced and reference genomes. We offer an alternative interpretation of the sequencing data of meiotic products, including the number and type of recombination events, to illustrate the potential for mistakes in single-nucleotide polymorphism calling. Using these examples, we propose that the detection of DNA polymorphisms using resequencing data needs to account for nonallelic homologous sequences.DNA polymorphisms are ubiquitous genetic variations among individuals and include single nucleotide polymorphisms (SNPs), insertions and deletions (indels), and other larger rearrangements (1–3) (Fig. 1 A and B). They can have phenotypic consequences and also serve as molecular markers for genetic analyses, facilitating linkage and association studies of genetic diseases, and other traits in humans (4–6), animals, plants, (7–10) and other organisms. Using DNA polymorphisms for modern genetic applications requires low-error, high-throughput analytical strategies. Here, we illustrate the use of short-read next-generation sequencing (NGS) data to detect DNA polymorphisms in the context of whole-genome analysis of meiotic products.Open in a separate windowFig. 1.(A) SNPs and small indels between two ecotype genomes. (B) Possible types of SVs. Col genotypes are marked in blue and Ler in red. Arrows indicate DNA segments involved in SVs between the two ecotypes. (C) Meiotic recombination events including a CO and a GC (NCO). Centromeres are denoted by yellow dots.There are many methods for detecting SNPs (11–14) and structural variants (SVs) (15–25), including NGS, which can capture nearly all DNA polymorphisms (26–28). This approach has been widely used to analyze markers in crop species such as rice (29), genes associated with diseases (6, 26), and meiotic recombination in yeast and plants (30, 31). However, accurate identification of DNA polymorphisms can be challenging, in part because short-read sequencing data have limited information for inferring chromosomal context.Genomes usually contain repetitive sequences that can differ in copy number between individuals (26–28, 31); therefore, resequencing analyses must account for chromosomal context to avoid mistaking highly similar paralogous sequences for polymorphisms. Here, we use recently published datasets to describe several DNA sequence features that can be mistaken as allelic (32, 33) and describe a strategy for differentiating between repetitive sequences and polymorphic alleles. We illustrate the effectiveness of these analyses by examining the reported polymorphisms from the published datasets.Meiotic recombination is initiated by DNA double-strand breaks (DSBs) catalyzed by the topoisomerase-like SPORULATION 11 (SPO11). DSBs are repaired as either crossovers (COs) between chromosomes (Fig. 1C), or noncrossovers (NCOs). Both COs and NCOs can be accompanied by gene conversion (GC) events, which are the nonreciprocal transfer of sequence information due to the repair of heteroduplex DNA during meiotic recombination. Understanding the control of frequency and distribution of CO and NCO (including GC) events has important implications for human health (including cancer and aneuploidy), crop breeding, and the potential for use in genome engineering. COs can be detected relatively easily by using polymorphic markers in the flanking sequences, but NCO products can only be detected if they are accompanied by a GC event. Because GCs associated with NCO result in allelic changes at polymorphic sites without exchange of flanking sequences, they are more difficult to detect. Recent advances in DNA sequencing have made the analysis of meiotic NCOs more feasible (30–32, 34); however, SVs present a challenge in these analyses. We recommend a set of guidelines for detection of DNA polymorphisms by using genomic resequencing short-read datasets. These measures improve the accuracy of a wide range of analyses by using genomic resequencing, including estimation of COs, NCOs, and GCs.     

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.     

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.     

Mechanical force effect on the two-state equilibrium of the hyaluronan-binding domain of CD44 in cell rolling

CD44 is the receptor for hyaluronan (HA) and mediates cell rolling under fluid shear stress. The HA-binding domain (HABD) of CD44 interconverts between a low-affinity, ordered (O) state and a high-affinity, partially disordered (PD) state, by the conformational change of the C-terminal region, which is connected to the plasma membrane. To examine the role of tensile force on CD44-mediated rolling, we used a cell-free rolling system, in which recombinant HABDs were attached to beads through a C-terminal or N-terminal tag. We found that the rolling behavior was stabilized only at high shear stress, when the HABD was attached through the C-terminal tag. In contrast, no difference was observed for the beads coated with HABD mutants that constitutively adopt either the O state or the PD state. Steered molecular dynamics simulations suggested that the force from the C terminus disrupts the interaction between the C-terminal region and the core of the domain, thus providing structural insights into how the mechanical force triggers the allosteric O-to-PD transition. Based on these results, we propose that the force applied from the C terminus enhances the HABD–HA interactions by inducing the conformational change to the high-affinity PD transition more rapidly, thereby enabling CD44 to mediate lymphocyte trafficking and hematopoietic progenitor cell homing under high-shear conditions.Leukocyte extravasation from blood to sites of infection and inflammation or to specific organs is achieved by a sequential adhesion cascade: (i) rolling, (ii) chemokine-induced activation, (iii) firm adhesion, and (iv) transcellular migration. Rolling is mediated by specialized cell surface adhesion molecules, such as selectins, CD44, and specific types of integrins (1, 2).Under conditions of hydrodynamic flow, receptor–ligand bonds are subjected to tensile mechanical force, which disrupts the receptor–ligand bond (Fig. 1A). In general, the lifetime of the receptor–ligand bond exponentially decreases with an increase of the mechanical force (3). However, there is growing evidence demonstrating that the lifetimes of some receptor–ligand bonds increase when moderate levels of force are applied (4–9). However, the underlying mechanism of this phenomenon is still elusive and in some cases controversial. For example, integrin and bacterial adhesin FimH-mediated adhesion have been explained by an “allosteric model,” in which mechanical force induces allosteric changes of the receptor, resulting in the stabilization of the high-affinity state (10, 11). Although selectin-mediated adhesion has been explained by the allosteric model (12), a different “sliding-rebinding model” was also reported (13). This model proposes that force tilts the binding interface to make it parallel to the direction of force, allowing the selectin ligand to slide on the selectin and to form new contacts. The sliding-rebinding model has also been used to explain the force-induced activation of von Willebrand factor-mediated adhesion and actin depolymerization (6, 8).Fig. 1.The effect of the tensile force on the two-state conformations of CD44 HABD. (A) Illustration of the tensile force applied between the receptor on the cells and the immobilized ligand under the fluid shear force. (B) The crystal structure of CD44 HABD ...CD44 is a transmembrane receptor for hyaluronan (HA) (14). CD44–HA interactions are involved in various physiological and pathological processes mediated over a wide range of hydrodynamic forces, including T-lymphocyte trafficking on the endothelium (15, 16), hematopoietic progenitor cell homing into bone marrow niches (17), and the progression of atherosclerosis (18). The HA-binding domain (HABD) of CD44 adopts two distinctive conformations representing the low- and high-affinity states for HA (19–21). HABD is composed of a conserved Link module and the N- and C-terminal extension segment (22). In the ordered (O) state, the C-terminal segment is well folded (Fig. 1B) (19), whereas it becomes disordered in the partially disordered (PD) state upon ligand binding (Fig. 1C) (20). In addition, solution NMR analyses demonstrated that HABD exists in an equilibrium between the O and PD states in both the HA-unbound and HA-bound states, with a transition rate of ∼500 ms, and that HA binding induces an equilibrium shift toward the PD state (21) (Fig. 1D). The Y161A mutant, which constitutively adopts the PD state, exhibits a higher affinity than wild-type HABD, indicating that the O and PD states represent the low- and high-affinity states for HA, respectively (21) (Fig. 1E). Cells expressing the Y161A mutant exhibited firm adhesion and impaired rolling on an HA substrate, suggesting that the two-state conformations are essential for the CD44-mediated rolling under flow conditions (21).Despite the importance of the mechanical force in rolling, the means by which it affects the CD44-mediated rolling remain poorly characterized. Recently, it was reported that the rolling of CD44-expressing cells is enhanced at the higher shear stress (23), raising the possibility that CD44 possesses some mechanochemical specializations to resist higher tensile force. Considering the fact that the C terminus of CD44 HABD is connected to the plasma membrane, the force applied from the C terminus of HABD would induce the allosteric transition from the O to the PD state, thereby providing the resistance to the applied force. On the other hand, our previous NMR studies demonstrated that more than 90% of HABD adopts the PD state in the HA-bound state (21), indicating that the free energy of the PD state can be lowered upon HA binding, regardless of the presence or absence of the tensile force. Therefore, it is worthwhile to investigate whether the CD44–HA interaction is strengthened by the tensile force.To assess the effect of the tensile force on the CD44-mediated rolling, we established a cell-free rolling system using cell-sized beads, which are coated with recombinant HABDs. The effect of the tensile force can be investigated by comparing the rolling activity of the beads coated with the ligand-binding domain via the N-terminal or the C-terminal tag (Fig. 1G) (10). We compared the rolling behavior of the beads with N- or C-terminally attached HABD and found that the rolling behavior was stabilized only at higher shear stress, when HABD was attached to the beads via the C-terminal tag. Steered molecular dynamics (SMD) simulations suggested that the force from the C terminus induces the dissociation of the “mechanosensitive latch” in the C-terminal region, which triggers the conversion from the O to the PD state. Based on these results, we propose that the tensile force from the C terminus stabilizes the CD44–HA bond by inducing a rapid transition from the O to the PD state, thereby sustaining the CD44-mediated cell rolling under higher shear stress conditions.     

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.     

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.     

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.