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.     

From the Cover: Hemozoin-generated vapor nanobubbles for transdermal reagent- and needle-free detection of malaria

Successful diagnosis, screening, and elimination of malaria critically depend on rapid and sensitive detection of this dangerous infection, preferably transdermally and without sophisticated reagents or blood drawing. Such diagnostic methods are not currently available. Here we show that the high optical absorbance and nanosize of endogenous heme nanoparticles called “hemozoin,” a unique component of all blood-stage malaria parasites, generates a transient vapor nanobubble around hemozoin in response to a short and safe near-infrared picosecond laser pulse. The acoustic signals of these malaria-specific nanobubbles provided transdermal noninvasive and rapid detection of a malaria infection as low as 0.00034% in animals without using any reagents or drawing blood. These on-demand transient events have no analogs among current malaria markers and probes, can detect and screen malaria in seconds, and can be realized as a compact, easy-to-use, inexpensive, and safe field technology.Rapid, accurate, noninvasive, and bloodless detection of low levels of malaria parasites is critical for surveillance, treatment, and elimination of malaria (1, 2) but so far is not supported by current diagnostic methods (3–7), which depend upon qualified personnel, sophisticated in vitro methodologies, blood sampling, and specific reagents. All blood-stage malaria parasites digest hemoglobin and form unique intraparasite nanoparticles called “hemozoin” (8–11). The high optical absorbance combined with the nanosize (50–400 nm) of hemozoin (9, 11, 12) can be used to generate a transient localized vapor nanobubble around hemozoin in response to a short, safe laser pulse. A short picosecond pulse localizes the released heat to a nanovolume around a nanoparticle (13, 14) and evaporates liquid around the hemozoin in an explosive manner, creating an expanding and collapsing transient vapor bubble of submicrometer size in the malaria parasite (Fig. 1A). Using our experience in the generation and detection of vapor nanobubbles of other origins in cells and animals (15, 16), we hypothesized that hemozoin-induced vapor nanobubbles (H-VNBs) can act as highly sensitive optical and acoustic probes for malaria detection (Fig. 1 B and C). Here, we report studies of H-VNBs in water, whole blood, and individual human red blood cells (RBCs) infected with Plasmodium falciparum and evaluate their noninvasive transdermal detection in Plasmodium yoelii–infected mice.Open in a separate windowFig. 1.(A) Laser-induced generation of a transient H-VNB around hemozoin nanoparticles inside a malaria parasite within the iRBC. Detection of optical scattering signals of the nanobubble with an optical detector (OD) (B) and (C) pressure pulse of the H-VNB detected with an ultrasound transducer (UT) as an acoustic trace.     

Bacterial lipids activate,synergize, and inhibit a developmental switch in choanoflagellates

In choanoflagellates, the closest living relatives of animals, multicellular rosette development is regulated by environmental bacteria. The simplicity of this evolutionarily relevant interaction provides an opportunity to identify the molecules and regulatory logic underpinning bacterial regulation of development. We find that the rosette-inducing bacterium Algoriphagus machipongonensis produces three structurally divergent classes of bioactive lipids that, together, activate, enhance, and inhibit rosette development in the choanoflagellate Salpingoeca rosetta. One class of molecules, the lysophosphatidylethanolamines (LPEs), elicits no response on its own but synergizes with activating sulfonolipid rosette-inducing factors (RIFs) to recapitulate the full bioactivity of live Algoriphagus. LPEs, although ubiquitous in bacteria and eukaryotes, have not previously been implicated in the regulation of a host–microbe interaction. This study reveals that multiple bacterially produced lipids converge to activate, enhance, and inhibit multicellular development in a choanoflagellate.The foundational event in animal origins—the transition to multicellularity (1–3)—occurred in oceans filled with diverse bacteria (4–7). There is a growing appreciation that specific bacteria direct diverse animal developmental processes, including light organ development in the Hawaiian bobtail squid and immune system development and maturation in organisms as diverse as cnidaria and mammals (8–20). However, the multicellularity of animals and the complex communities of bacteria with which they often interact hinder the complete characterization of many host–microbe dialogues.Choanoflagellates, a group of microbial eukaryotes that are the closest living relatives of animals (21–24), promise to help illuminate the mechanisms by which bacteria influence animal development. As did cells in the first animals, choanoflagellates use a distinctive collar of actin-filled microvilli surrounding a flow-generating apical flagellum to capture bacteria as prey (25–27). Indeed, choanoflagellate-like cells likely formed the basis for the evolution of animal epithelial cells that today provide a selective barrier for mediating interactions with bacteria (27–29).In many choanoflagellates, including Salpingoeca rosetta, a developmental program can be initiated such that single cells develop into multicellular rosettes. Importantly, rosette development does not occur through cell aggregation. Instead, as in the development of an animal from a zygote, rosettes develop from a single founding cell that undergoes serial rounds of oriented cell division, with the sister cells remaining stably adherent (Fig. 1). The orientation of the nascently divided cells around a central focus, the production of extracellular matrix, and the activity of a C-type lectin called Rosetteless, ultimately result in the formation of spherical, multicellular rosettes (30–32). Rosettes resemble morula-stage embryos, and the transition to multicellularity in S. rosetta evokes ancestral events that spawned the first animals (26, 27, 33).Open in a separate windowFig. 1.Stages of rosette development in S. rosetta. During rosette development, a single founding cell undergoes serial rounds of cell division, resulting in a structurally integrated rosette. Importantly, rosette development does not involve cell aggregation. Shown are a single cell (A), a pair of cells (B), a 4-cell rosette (C), an 8-cell rosette (D) and a 16-cell rosette (E).The initiation of rosette development was recently found to be induced by a coisolated environmental bacterium, Algoriphagus machipongonensis (phylum Bacteroidetes) (34, 35). The ecological relevance of the interaction between A. machipongonensis (hereafter, Algoriphagus) and S. rosetta is evidenced by the coexistence of these organisms in nature (35) and the predator–prey relationship between choanoflagellates and bacteria (25, 36). Indeed, rosettes likely have a fitness advantage over single cells in some environments, as multicellular choanoflagellates are predicted to produce increased flux of water past each cell (37), and prey capture studies reveal that rosettes collect more bacterial prey/cell/unit time than do single cells (38). However, in other environments, rosette development would likely reduce fitness as rosettes have reduced motility relative to single cells. Therefore, we hypothesize that choanoflagellates use bacterially produced molecules to identify environments in which rosette development might provide a fitness advantage.The simplicity of the interaction between S. rosetta and Algoriphagus, in which both members can be cultured together or independently, offers a biochemically tractable model for investigating the molecular bases of bacteria–eukaryote interactions. Using rosette development as a bioassay, the first rosette-inducing molecule, Rosette Inducing Factor-1 (RIF-1), was isolated from Algoriphagus. The observation that RIF-1 fails to fully recapitulate the bioactivity of the live bacterium (Fig. 2 A and C) raised the possibility that additional molecules might be required (35). To gain a more complete understanding of the molecules and regulatory logic by which bacteria regulate rosette development, we set out to identify the minimal suite of molecules produced by Algoriphagus that are necessary and sufficient to regulate rosette development in S. rosetta.Open in a separate windowFig. 2.Maximal rosette development requires lipid cofactor interactions. (A) When treated with media that lack necessary bacterial signals (Media Control), S. rosetta does not produce rosettes. In contrast, when treated with live Algoriphagus, Algoriphagus-conditioned media, OMVs from Algoriphagus, or bulk lipids extracted from Algoriphagus, rosettes develop at maximal (∼90% cells in rosettes) or near-maximal levels. (B) A heat map depicts the rosette-inducing activity of Algoriphagus lipid fractions used to treat SrEpac, either in isolation or in combination, at a final lipid concentration of 2 μg/mL Sulfonolipid-enriched fraction 11 was the only fraction sufficient to induce rosette development when tested alone (30% of cells in rosettes). Tests of each of the lipid fractions in combination revealed previously unidentified inhibitory and enhancing activity. Fractions 4 and 5 decreased rosette development (to 12% and 8%, respectively) in fraction 11-treated cells, whereas fraction 7 increased rosette development to 65%. (C) The RIF mix (solid square) and purified RIF-2 (solid circle) induced rosette development at micromolar concentrations. (Inset) RIF-1 (open circle) is active at femtomolar to nanomolar concentrations, but induces 10-fold lower levels of rosette development than RIF-2. The long gray box in the main graph indicates the range of concentrations at which RIF-1 is active and the range of its rosette-inducing activity. Rosette development was quantified 24 h after induction. Minor ticks on x axis are log-spaced.     

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.     

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.     

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.     

Gate-controlled proton diffusion and protonation-induced ratchet motion in the stator of the bacterial flagellar motor

The proton permeation process of the stator complex MotA/B in the flagellar motor of Escherichia coli was investigated. The atomic model structure of the transmembrane part of MotA/B was constructed based on the previously published disulfide cross-linking and tryptophan scanning mutations. The dynamic permeation of hydronium/sodium ions and water molecule through the channel formed in MotA/B was observed using a steered molecular dynamics simulation. During the simulation, Leu46 of MotB acts as the gate for hydronium ion permeation, which induced the formation of water wire that may mediate the proton transfer to Asp32 on MotB. Free energy profiles for permeation were calculated by umbrella sampling. The free energy barrier for H₃O⁺ permeation was consistent with the proton transfer rate deduced from the flagellar rotational speed and number of protons per rotation, which suggests that the gating is the rate-limiting step. Structure and dynamics of the MotA/B with nonprotonated and protonated Asp32, Val43Met, and Val43Leu mutants in MotB were investigated using molecular dynamics simulation. A narrowing of the channel was observed in the mutants, which is consistent with the size-dependent ion selectivity. In MotA/B with the nonprotonated Asp32, the A3 segment in MotA maintained a kink whereas the protonation induced a straighter shape. Assuming that the cytoplasmic domain not included in the atomic model moves as a rigid body, the protonation/deprotonation of Asp32 is inferred to induce a ratchet motion of the cytoplasmic domain, which may be correlated to the motion of the flagellar rotor.Bacterial flagella are multifuel engines that convert ion motive force to molecular motor rotation. Escherichia coli has a few proton-driven flagellar motors with stators (protein MotA/B complex) in the inner membrane that act as proton channels (1–5). In addition, Vibrio alginolyticus has a polar flagellum powered by sodium ions (6). Bacillus alcalophilus has motors driven by rubidium (Rb⁺), potassium (K⁺), and sodium ions (Na⁺) that can be converted to Na⁺-driven motors by a single mutation (7).The proton transfer mechanism in membrane proteins is associated with water wire and/or a hydrogen bond chain (HBC) (8, 9). The water wire comprises water molecules aligned in a protein channel, where protons are transferred by hopping along the wire. Protons are conducted through the hydrogen bonds formed by the polar amino acid residues and water molecules along the proton transfer pathway in the HBC. Protons can also be transferred by diffusion of hydronium ions (H₃O⁺). The diffusion distance in a hydrophilic environment is short in a liquid (the lifetime in water is ca. 1 ps) (10, 11), but it should be longer in a more hydrophobic environment. H₃O⁺ forms a hydrogen bond (H bond) with the nearest neighbor water molecules and the carbonyl groups, and proton hopping along the H bonds is faster than diffusion of Na⁺ and K⁺ in the ion channel of Gramicidin A (12, 13).These flagellar motors can rotate in both clockwise (CW) and counterclockwise (CCW) directions (viewed from the outside of the cell), and the swimming pattern of the bacteria is controlled by reversal of the motor rotation (14). In E. coli, the FliG, FliM, FliN, MotA, and MotB proteins are involved with torque generation (Fig. 1A) (14, 15). FliG, FliM, and FliN constitute the flagellar rotor and are also involved with the CW/CCW switching. Each rotor is typically surrounded by 10 stators that consist of two membrane proteins, MotA and MotB (PomA and PomB in V. alginolyticus). Each stator is composed of four MotA and two MotB proteins, and can independently produce torque for flagellar rotation.Open in a separate windowFig. 1.Overall structure of MotA/B. (A) Schematic views of the flagellar motors of E. coli (Left) and V. alginolyticus (Right), (B) TM regions modeled, and (C) TM helix arrangement in the initial modeling of MotA/B in E. coli. The obtained atomic model structure viewed parallel to the membrane (D) and from the periplasmic side (E). Spheres denote P atoms in the lipid head groups. MotA/B cross sections of the area enclosed by magenta in E around a channel at the levels of Leu46 (F) and Asp32 (G). x, y, and z axes are defined as in D and E.Systematic Cys and Trp mutagenesis (16–20) has provided essential information on the structure and function of the flagellar motor. Each MotA (295 residues) contains four transmembrane (TM) alpha helical segments (A1–A4), two short loops in the periplasm, and two long segments (residues 61–160 and 228–295) in the cytoplasm (Fig. 1B) (3, 21). Arg90 and Glu98 on the MotA cytoplasmic domain interact with the polar residues on the rotor protein, FliG, during the rotation of the motor (22, 23). It has been suggested that Pro173 and Pro222 at the cytoplasmic sides of A3 and A4 regulate the conformational changes required for torque generation (24). MotB (308 residues) is composed of a short N-terminal cytoplasimic segment, one TM helix (B), and a large C-terminal periplasmic domain (Fig. 1B) (4, 5). Asp32, which is situated near the cytoplasmic end of the B segment, is conserved across the species and considered to be the most plausible proton binding site (25). The B segment is expected to form a proton channel together with A3 and A4 (Fig. 1C) (17). Only a few polar residues have been identified in the predicted TM segments of MotA/B (19, 20), which implies that the channel surface should be relatively hydrophobic. The periplasmic region of MotB has a peptidoglycan binding motif, which anchors the stator complex to the peptidoglycan layer around the rotor (5, 26). Deletion of residues 52–65 just after the B segment causes proton leakage and cell growth arrest, which suggests that this fragment acts as a plug to suppress proton leakage (27). The generation of torque is hypothesized to originate from the conformational changes of the MotA cytoplasmic domain upon proton association/dissociation at the carboxyl group of Asp32 on MotB and by the interaction with FliG in the rotor (28–31).In the present study, the mechanism for proton permeation in MotA/B was investigated (Fig. S1). The atomic structure of MotA/B was constructed based on the disulfide cross-linking (16–18) and tryptophan scanning mutations (19, 20). The dynamic permeation of hydronium ions, sodium ions, and water molecules was observed using a steered molecular dynamics (SMD) simulation (32–34), and free energy profiles for ion/water permeation were calculated by umbrella sampling. The effects of amino acid substitutions related to ion selectivity was investigated, and the possible ratchet motion of the cytoplasmic domain induced by protonation/deprotonation cycle of Asp32 was examined.Open in a separate windowFig. S1.Overall scheme of this study.     

Quantum delocalization of protons in the hydrogen-bond network of an enzyme active site

Enzymes use protein architectures to create highly specialized structural motifs that can greatly enhance the rates of complex chemical transformations. Here, we use experiments, combined with ab initio simulations that exactly include nuclear quantum effects, to show that a triad of strongly hydrogen-bonded tyrosine residues within the active site of the enzyme ketosteroid isomerase (KSI) facilitates quantum proton delocalization. This delocalization dramatically stabilizes the deprotonation of an active-site tyrosine residue, resulting in a very large isotope effect on its acidity. When an intermediate analog is docked, it is incorporated into the hydrogen-bond network, giving rise to extended quantum proton delocalization in the active site. These results shed light on the role of nuclear quantum effects in the hydrogen-bond network that stabilizes the reactive intermediate of KSI, and the behavior of protons in biological systems containing strong hydrogen bonds.Although many biological processes can be well-described with classical mechanics, there has been much interest and debate as to the role of quantum effects in biological systems ranging from photosynthetic energy transfer, to photoinduced isomerization in the vision cycle and avian magnetoreception (1). For example, nuclear quantum effects, such as tunneling and zero-point energy (ZPE), have been observed to lead to kinetic isotope effects of greater than 100 in biological proton and proton-coupled electron transfer processes (2, 3). However, the role of nuclear quantum effects in determining the ground-state thermodynamic properties of biological systems, which manifest as equilibrium isotope effects, has gained significantly less attention (4).Ketosteroid isomerase (KSI) possesses one of the highest enzyme unimolecular rate constants and thus, is considered a paradigm of proton transfer catalysis in enzymology (5–11). The remarkable rate of KSI is intimately connected to the formation of a hydrogen-bond network in its active site (Fig. 1A), which acts to stabilize a charged dienolate intermediate, lowering its free energy by ∼11 kcal/mol (1 kcal = 4.18 kJ) relative to solution (Fig. S1) (6). This extended hydrogen-bond network in the active site links the substrate to Asp103 and Tyr16, with the latter further hydrogen-bonded to Tyr57 and Tyr32, which is shown in Fig. 1A.Open in a separate windowFig. 1.KSI⋅intermediate and KSI^D40N ? inhibitor complex. Schematic depiction of (A) the KSI⋅intermediate complex during the catalytic cycle (Fig. S1) and (B) a complex between KSI^D40N and phenol, an inhibitor that acts as an intermediate analog. Both the intermediate and the inhibitor are stabilized by a hydrogen-bond network in the active site of KSI. (C) Image of KSI^D40N with the tyrosine triad enlarged and the atoms O16, H16, O32, H32, and O57 labeled (shown with Tyr57 deprotonated) (16).The mutant KSI^D40N preserves the structure of the wild-type (WT) enzyme while mimicking the protonation state of residue 40 in the intermediate complex (Fig. 1B), therefore permitting experimental investigation of an intermediate-like state of the enzyme (6, 12–14). Experiments have identified that, in the absence of an inhibitor, one of the residues in the active site of KSI^D40N is deprotonated (12). Although one might expect the carboxylic acid of Asp103 to be deprotonated, the combination of recent ¹³C NMR and ultraviolet visible spectroscopy (UV-Vis) experiments has shown that the ionization resides primarily on the hydroxyl group of Tyr57, which possesses an anomalously low pK_a of 6.3 ± 0.1 (12). Such a large tyrosine acidity is often associated with specific stabilizing electrostatic interactions (such as a metal ion or cationic residue in close proximity), which is not the case here, suggesting that an additional stabilization mechanism is at play (15).One possible explanation is suggested by the close proximity of the oxygen (O) atoms on the side chains of the adjacent residues Tyr16 (O16) and Tyr32 (O32) to the deprotonated O on Tyr57 (O57) (Fig. 1C) (16). In several high-resolution crystal structures, these distances are found to be around 2.6 Å (14, 16, 17), which is much shorter than those observed in hydrogen-bonded liquids such as water, where O–O distances are typically around 2.85 Å. Such short heavy-atom distances are only slightly larger than those typically associated with low-barrier hydrogen bonds (18–20), where extensive proton sharing is expected to occur between the atoms. In addition, at these short distances, the proton’s position uncertainty (de Broglie wavelength) becomes comparable with the O–O distance, indicating that nuclear quantum effects could play an important role in stabilizing the deprotonated residue (Fig. 1C). In this work, we show how nuclear quantum effects determine the properties of protons in the active-site hydrogen-bond network of KSI^D40N in the absence and presence of an intermediate analog by combining ab initio path integral simulations and isotope effect experiments.     

Cortical thickness of the dorsolateral prefrontal cortex predicts strategic choices in economic games

Human prosociality has been traditionally explained in the social sciences in terms of internalized social norms. Recent neuroscientific studies extended this traditional view of human prosociality by providing evidence that prosocial choices in economic games require cognitive control of the impulsive pursuit of self-interest. However, this view is challenged by an intuitive prosociality view emphasizing the spontaneous and heuristic basis of prosocial choices in economic games. We assessed the brain structure of 411 players of an ultimatum game (UG) and a dictator game (DG) and measured the strategic reasoning ability of 386. According to the reflective norm-enforcement view of prosociality, only those capable of strategically controlling their selfish impulses give a fair share in the UG, but cognitive control capability should not affect behavior in the DG. Conversely, we support the intuitive prosociality view by showing for the first time, to our knowledge, that strategic reasoning and cortical thickness of the dorsolateral prefrontal cortex were not related to giving in the UG but were negatively related to giving in the DG. This implies that the uncontrolled choice in the DG is prosocial rather than selfish, and those who have a thicker dorsolateral prefrontal cortex and are capable of strategic reasoning (goal-directed use of the theory of mind) control this intuitive drive for prosociality as a means to maximize reward when there are no future implications of choices.Humans are a cooperative species, and the question of why humans are so cooperative has been a subject of considerable interest in social and biological sciences (1–4). The traditional answer in the social sciences highlights critical roles of social norms and cultural values internalized as personal values and social preferences (5, 6). Recent neuroscientific studies of brain structure and activity extended this traditional view of human prosociality by showing that players of economic games act prosocially when they cognitively control selfish impulses (7–13). Experimental evidence shows that prosocial choices in economic games positively relate to local gray matter volume and thickness and the activation of brain areas that control selfish impulsive drives, such as the dorsolateral prefrontal cortex (DLPFC) and temporoparietal junction (TPJ) (7–9). Furthermore, impairment of cognitive control by disruption of DLPFC function prevents rejection of unfair offers in the ultimatum game (UG), which some authors considered prosocial and fairness-seeking behavior (10–13). Recently, this reflective view of human prosociality has been challenged by an alternative view emphasizing the intuitive nature of prosocial behavior, subsumed under intuitive prosociality (14) or heuristic cooperation (15–17). Support for the intuitive and automatic nature of prosocial behavior is provided by findings that prosocial choices are promoted under time pressure (15, 16, 18), under cognitive load (19–21), or after priming by successful experiences of intuitive decision making (15, 22). Also, participants who expressed more positive emotional words and less inhibitory words during and after an economic game cooperated more (23). Additionally, increased activity in the lateral prefrontal cortex was negatively related to fairness-seeking behavior in an economic game (24). According to the heuristic prosociality model (14–17), humans are predisposed to cooperate in social exchange situations. People fail to behave in a prosocial manner in social exchanges when this predisposition is overridden by strategic reasoning to secure their self-interest. By comparing participants’ behaviors in two economic games with brain structural differences and strategic reasoning abilities, we provide evidence that strategic reasoning controls, and thus reduces rather than promotes, game players’ prosocial behavior.The contrast between two simple, two-person economic games—namely, the dictator game (DG) and the UG—is often used to support the reflective prosocial model by demonstrating how strategic reasoning affects game players’ decisions. In both games, one player freely decides how much of a fixed reward to take and how much to leave for the other player. The difference between the two games is that the other player in the UG (termed “responder”) has the option to reject the decision made by the first player (termed “proposer”), causing both to earn nothing. This option is not provided to the second player in the DG, who plays the role of a “recipient”. The recipient simply receives whatever the first player (“dictator”) gives. The level of giving by the proposer in the UG is usually higher than that by the dictator in the DG (25). This is attributed to the proposer’s strategic reasoning, which requires inference of the recipient’s internal state and prediction of the resulting response (e.g., anger on the basis of unfair giving and subsequent rejection) (8, 9, 13). Given that neuroimaging and neuroendocrinological studies showed that negative emotions are associated with rejection of unfair offers (24, 26, 27), UG proposers may anticipate negative responses to unfair offers. UG proposers anticipate norm-enforcing responses (rejection of the offer) to norm-violating behavior (taking most of the reward) and strategically adjust giving behavior to secure acceptance by the responder. Thus, those capable of using strategic reasoning are expected to make fair offers in the UG compared with those who struggle to control their selfish drive for immediate reward.In contrast, in the DG, which requires no strategic reasoning to earn as much as possible, strategic control over selfish impulses is expected not to influence the player’s choices. Spitzer et al. (9) confirmed this by showing a positive correlation between the difference in giving in the UG and the DG (i.e., a measure of strategic reasoning) and activity of the right DLPFC and the lateral orbitofrontal cortex. Given earlier findings implicating the DLPFC in cognitive control of impulsive behavior (28–33), this is taken to support the reflective model of prosociality, in which prosocial behavior requires cognitive control of the impulsive drive toward selfish behavior. Steinbeis et al. (8) provided further support via a comparison of young children’s choices in the two economic games. Children took a large share in the DG while providing fairer amounts to responders in the UG. The children’s more generous giving in the UG may be based upon strategic reasoning regarding the possible consequences of not giving enough in the UG—that is, receiving no reward due to rejection by the other child—which plays no role in the DG. Thus, the difference in giving between the UG and the DG is considered to reflect the use of strategic reasoning in the UG. The strategic choices of more giving in the UG than in the DG is related to children’s age, cortical thickness, and activity of their left DLPFC. As children age and their DLPFC develops further, they become able to control their selfish drive and adjust their behavior to the anticipated negative consequences.This interpretation of UG–DG difference in prosocial giving as a reflection of strategic reasoning (8, 9) assumes that the default choice in the DG is impulsive and selfish. Younger children and those with a thinner DLPFC are presumably less capable of strategically adjusting their decisions to deal with anticipated responses and would impulsively pursue their own benefits in both the UG and the DG. In contrast, older children and those with a thicker DLPFC are more likely to have enhanced cognitive control, which can be used to strategically adjust their choices, especially in the UG but not in the DG. Therefore, a UG–DG positive reward transfer difference is produced by strategists’ control over the selfish impulses in the UG, whereas those who fail to control such impulses in the UG claim a considerable share in both games (Fig. 1A). In contrast, the alternative, intuitive prosociality model assumes that the uncontrolled choice is prosocial in both the UG and the DG, rather than selfish. Strategists control this impulse toward prosociality in the DG where immediate pursuit of self-interest causes no strategic problem (Fig. 1B). Nonstrategists do not control this impulse and provide a fair share in both games. Thus, a difference due to strategic reasoning is predicted to exist in the DG but not in the UG. The reflective and intuitive prosociality models thus make distinct predictions regarding the relationship between DLPFC thickness and behavior in the UG and DG. The reflective model predicts a positive relationship between DLPFC thickness and giving in the UG, whereas the intuitive model predicts a negative relationship between DLPFC thickness and giving in the DG.Open in a separate windowFig. 1.Schematic representations of how strategic considerations generate the difference between strategists (ST) and nonstrategists (Non-ST) in the UG and DG. A shows the prediction that strategic considerations should improve fair behavior in the UG. B shows the prediction that strategic considerations should depress fair behavior in the DG.These two alternative accounts of differences in giving in the UG and DG (8, 9) provide a way to test the intuitive selfishness assumption against the intuitive prosociality assumption. We first successfully replicated earlier findings that strategic behavior is more pronounced among those who had a thicker DLPFC than those who had a thinner DLPFC (8) in a study of 411 adult, nonstudent participants who played both the UG and DG and from whom brain structural images were obtained. Then, we found for the first time, to our knowledge, that local gray matter thickness of the DLPFC negatively correlated with giving in the DG but was not correlated with giving in the UG (Fig. 2 C and D). We further measured the strategic reasoning of 386 of these participants using a newly developed test of strategic reasoning, measured 411 participants’ Machiavellianism (34, 35) score, and found that those exhibiting better strategic reasoning behaved more selfishly in the DG than those with poor strategic reasoning, but no relationship was found between task performance and fairness in the UG. These striking findings provide strong evidence supporting the intuitive prosociality prediction depicted in Fig. 1B but not the reflective prosociality prediction shown in Fig. 1A.Open in a separate windowFig. 2.Brain areas in the Destrieu Atlas (A), the relationship of cortical thickness of the DLPFC (middle frontal gyrus) and strategic choice (UG–DG) (B), the relationship of its right cortical thickness and giving in the UG and DG (C), and the relationship of its left cortical thickness and giving in the UG and DG (D). The horizontal axis represents the residual cortical thickness adjusted for participants’ age, sex, and ICV. The vertical axis represents the mean strategic choice of the players, giving in the UG or the DG within 0.1-mm intervals of residual cortical thickness. Each interval spans 0.1 mm on the horizontal axis segment. The size of each circle shows the number of players who fell within the interval. Error bars are SEs. n = 411. Correlations are after adjusting for age, sex, and ICV.     

An intramolecular lock facilitates folding and stabilizes the tertiary structure of Streptococcus mutans adhesin P1

The cariogenic bacterium Streptococcus mutans uses adhesin P1 to adhere to tooth surfaces, extracellular matrix components, and other bacteria. A composite model of P1 based on partial crystal structures revealed an unusual complex architecture in which the protein forms an elongated hybrid alpha/polyproline type II helical stalk by folding back on itself to display a globular head at the apex and a globular C-terminal region at the base. The structure of P1’s N terminus and the nature of its critical interaction with the C-terminal region remained unknown, however. We have cocrystallized a stable complex of recombinant N- and C-terminal fragments and here describe a previously unidentified topological fold in which these widely discontinuous domains are intimately associated. The structure reveals that the N terminus forms a stabilizing scaffold by wrapping behind the base of P1’s elongated stalk and physically “locking” it into place. The structure is stabilized through a highly favorable ΔG_solvation on complex formation, along with extensive hydrogen bonding. We confirm the functional relevance of this intramolecular interaction using differential scanning calorimetry and circular dichroism to show that disruption of the proper spacing of residues 989–1001 impedes folding and diminishes stability of the full-length molecule, including the stalk. Our findings clarify previously unexplained functional and antigenic properties of P1.Streptococcus mutans is a recognized cause of human dental caries (cavities), the most common infectious disease worldwide (1). Identifying how S. mutans interacts with host components at the molecular level is essential to fully understand its virulence properties. The sucrose-independent adhesin P1 (AgI/II, antigen B, PAc) is localized on the surface of this oral pathogen, along with many other streptococci (2–7). In the oral cavity, S. mutans P1 interacts with the salivary agglutinin glycoprotein complex composed predominantly of scavenger receptor gp340/DMBT1 (2, 3, 5–10). Without a complete structural model, the mechanisms by which P1 binds to host components have not yet been fully characterized.P1’s primary structure (Fig. 1A) contains a 38-residue signal sequence, the heretofore uncharacterized N-terminal region, three alanine-rich repeats (A1–3), a central domain containing a so-called variable (V) region (11), three proline-rich repeats (P1–3), a C-terminal region consisting of three domains (C1–3), an LPxTG sortase-recognition motif, and wall- and membrane-spanning regions (12, 13). Recent partial X-ray crystal structure and velocity centrifugation studies of the intact protein unveiled a unique architecture in which the ∼185-kDa (1,561-aa) protein folds back on itself to form a ∼50-nm elongated hybrid helical stalk that separates two independent adherence domains, with a globular head at the apex and a globular C-terminal region at the base (13–15) (Fig. 1B).Open in a separate windowFig. 1.Schematic representation of the primary and modeled tertiary structure of P1. (A) Primary structure of P1 and location of polypeptides used in this study. (B) Proposed tertiary model of P1 based on velocity centrifugation and crystal structures of A3VP1 and C123 fragments (13). (C) Diagram showing the locations of the two engineered Cla1 sites (circled in red) that added isoleucine and aspartic acid residues to either side of the proline-rich region (20).The crystal structure of the third alanine-rich repeat through the first proline-rich repeat first revealed the unusual interaction between the A and P regions to form a hybrid alpha/polyproline type II helix (14). In this model, a globular β super sandwich domain sits at the apex of the molecule (15). At the other end of the hybrid helix, the three contiguous domains of the C-terminal region each adopt a DE-variant Ig-like (DEv-IgG) fold stabilized by isopeptide bonds (13, 16). Despite this recent progress, the structure of the ∼20-kDa N terminus of P1 remained unknown, however (Fig. 1B). We previously demonstrated that proper folding and function of P1 on the surface of S. mutans requires an interaction between N- and C-terminal segments (17), thus increasing the imperative to elucidate the structure of the N terminus in complex with its intramolecular binding partner.For this, we used the recombinant N-terminal (NA1) and C-terminal (P3C) P1 fragments (Fig. 1A), which have been shown to form a stable high-affinity and functionally active complex (17). The NA1/P3C protein complex was copurified and then cocrystallized for X-ray diffraction data collection to 2.0-Å resolution. We observed that the N terminus adopts a previously unidentified fold that serves as an intramolecular scaffold connecting it to C-terminal portions of the molecule, thus locking P1’s hybrid helical stalk into place. We validated this model experimentally using differential scanning calorimetry (DSC) and circular dichroism to demonstrate decreased thermal stability and altered secondary structure in a P1 mutant containing two extra amino acids within the region that normally reacts with the N-terminal intramolecular scaffold. Our X-ray crystallography model and stability measurements agree well with biophysical data characterizing the NA1/P3C complex (17) and provide mechanistic insight into why the N-terminal segment supports the proper folding, function, and stability of the full-length P1 protein. This information contributes to our ability to interpret data regarding protective and nonprotective immune responses and preventative therapies, and will inform future studies evaluating bacterial adhesion and biofilm formation by S. mutans and related organisms.     

Gyrification from constrained cortical expansion

The exterior of the mammalian brain—the cerebral cortex—has a conserved layered structure whose thickness varies little across species. However, selection pressures over evolutionary time scales have led to cortices that have a large surface area to volume ratio in some organisms, with the result that the brain is strongly convoluted into sulci and gyri. Here we show that the gyrification can arise as a nonlinear consequence of a simple mechanical instability driven by tangential expansion of the gray matter constrained by the white matter. A physical mimic of the process using a layered swelling gel captures the essence of the mechanism, and numerical simulations of the brain treated as a soft solid lead to the formation of cusped sulci and smooth gyri similar to those in the brain. The resulting gyrification patterns are a function of relative cortical expansion and relative thickness (compared with brain size), and are consistent with observations of a wide range of brains, ranging from smooth to highly convoluted. Furthermore, this dependence on two simple geometric parameters that characterize the brain also allows us to qualitatively explain how variations in these parameters lead to anatomical anomalies in such situations as polymicrogyria, pachygyria, and lissencephalia.The mammalian brain is functionally and anatomically complex. Over the years, accumulating evidence (1, 2) shows that there are strong anatomical correlates of its information-processing ability; indeed the iconic convoluted shape of the human brain is itself used as a symbol of its functional complexity. This convoluted (gyrified) shape is associated with the rapid expansion of the cerebral cortex. Understanding the evolutionary and developmental origins of the cortical expansion (1–6) and their mechanistic role in gyrification is thus an important question that needs to be answered to decipher the functional complexity of the brain.Historically there have been three broad hypotheses about the origin of sulci and gyri. The first is that gyri rise above sulci by growing more (7), requiring the pattern of sulci and gyri to be laid down before the cortex folds, presumably by a chemical morphogen. There is no evidence for this mechanism. The second hypothesis considers that the outer gray matter consists of neurons, and the inner white matter is largely long thin axons that connect the neurons to each other and to other parts of the nervous system and proposes that these axons pull mechanically, drawing together highly interconnected regions of gray matter to form gyri (8–10). However, recent experimental evidence (11) shows that axonal tension when present is weak and arises deep in the white matter and is thus insufficient to explain the strongly deformed gyri and sulci. The third hypothesis is that the gray matter simply grows more than the white matter, an experimentally confirmed fact, leading to a mechanical buckling that shapes the cortex (11–14). Evidence for this hypothesis has recently been provided by observations of mechanical stresses in developing ferret brains (11), which were found to be in patterns irreconcilable with the axonal tension hypothesis. In addition, experiments show that sulci and gyri can be induced in usually smooth-brained mice by genetic manipulations that promote cortical expansion (15, 16), suggesting that gyrification results from an unregulated and unpatterned growth of the cortex relative to sublayers.Nevertheless, there is as yet no explicit biologically and physically plausible model that can convincingly reproduce individual sulci and gyri, let alone the complex patterns of sulci and gyri found in the brain. Early attempts to mechanically model brain folding (13) were rooted in the physics of wrinkling and assumed a thin stiff layer of gray matter that grows relative to a thick soft substrate of white matter. This model falls short in two ways. First, the gray matter is neither thin nor stiff relative to the white matter (17, 18). Second, this model predicts smooth sinusoidal wrinkling patterns, sketched in Fig. 1A, whereas even lightly folded brains have smooth gyri but cusped sulci. More complicated mechanical models including, e.g., elasto-plasticity and stress-related growth (14, 19, 20), lead to varying morphologies, but all produced simple smooth convolutions rather than cusped sulci.Open in a separate windowFig. 1.Wrinkling and sulcification in a layered material subject to differential growth. (A) If the growing gray matter is much stiffer than the white matter it will wrinkle in a smooth sinusoidal way. (B) If the gray matter is much softer than the white matter its surface will invaginate to form cusped folds. (C) If the two layers have similar moduli the gray matter will both wrinkle and cusp giving gyri and sulci. Physical realizations of A, B, and C, based on differential swelling of a bilayer gel (Materials and Methods), confirm this picture and are shown in D, E, and F, respectively.A fundamentally different mechanical instability that occurs on the surface of a uniformly compressed soft solid (21, 22) has recently been exposed and clarified, theoretically, computationally, and experimentally (23–26). This sulcification instability arises under sufficient compression leading to the folding of the soft surface to form cusped sulci via a strongly subcritical transition. In Fig. 1B, we show a geometry dual to that associated with wrinkling: A soft layer of gray matter grows on a stiff white-matter substrate. Unlike wrinkling, this instability can produce the cusped centers of sulci, but the flat bottom of the gray matter is not seen in the brain. This is a consequence of the assumption that the gray matter is much softer than the white matter—in reality the two have very similar stiffnesses (17, 18). We are thus led to the final simple alternate, sketched in Fig. 1C, where the stiffnesses of the gray and white matter are assumed to be identical. Such a system is subject to a cusp-forming sulcification instability discussed earlier, and can lead to an emergent pattern very reminiscent of sulci and gyri in the brain.     

Dietary options and behavior suggested by plant biomarker evidence in an early human habitat

The availability of plants and freshwater shapes the diets and social behavior of chimpanzees, our closest living relative. However, limited evidence about the spatial relationships shared between ancestral human (hominin) remains, edible resources, refuge, and freshwater leaves the influence of local resources on our species’ evolution open to debate. Exceptionally well-preserved organic geochemical fossils—biomarkers—preserved in a soil horizon resolve different plant communities at meter scales across a contiguous 25,000 m² archaeological land surface at Olduvai Gorge from about 2 Ma. Biomarkers reveal hominins had access to aquatic plants and protective woods in a patchwork landscape, which included a spring-fed wetland near a woodland that both were surrounded by open grassland. Numerous cut-marked animal bones are located within the wooded area, and within meters of wetland vegetation delineated by biomarkers for ferns and sedges. Taken together, plant biomarkers, clustered bone debris, and hominin remains define a clear spatial pattern that places animal butchery amid the refuge of an isolated forest patch and near freshwater with diverse edible resources.Spatial patterns in archaeological remains provide a glimpse into the lives of our ancestors (1–5). Although many early hominin environments are interpreted as grassy or open woodlands (6–8), fossil bones and plant remains are rarely preserved together in the same settings. As a result, associated landscape reconstructions commonly lack coexisting fossil evidence for hominins and local-scale habitat (microhabitat) that defined the distribution of plant foods, refuge, and water (7). This problem is exacerbated by the discontinuous nature and low time resolution often available across ancient soil (paleosol) horizons, including hominin archaeological localities. One notable exception is well-time-correlated 1.8-million-y-old paleosol horizons exposed at Olduvai Gorge. Associated horizons contain exceptionally preserved plant biomarkers along with many artifacts and fossilized bones. Plant biomarkers, which previously revealed temporal patterns in vegetation and water (8), are well preserved in the paleosol horizon and document plant-type spatial distributions that provide an ecosystem context (9, 10) for resources that likely affected the diets and behavior of hominin inhabitants.Plant biomarkers are delivered by litter to soils and can distinguish plant functional type differences in standing biomass over scales of 1–1,000 m² (11). Trees, grasses, and other terrestrial plants produce leaf waxes that include long-chain n-alkanes such as hentriacontane (nC₃₁), whereas aquatic plants and phytoplankton produce midchain homologs (e.g., nC₂₃) (12, 13). The ratio of shorter- versus long-chain n-alkane abundances distinguish relative organic matter inputs from aquatic versus terrestrial plants to sediments (13):P_aq = (nC₂₃ + nC₂₅)/(nC₂₃ + nC₂₅ + nC₂₉ + nC₃₁).Sedges and ferns are prolific in many tropical ecosystems (14). These plants both have variable and therefore nondiagnostic n-alkane profiles. However, sedges produce distinctive phenolic compounds [e.g., 5-n-tricosylresorcinol (ⁿR₂₃)] and ferns produce distinctive midchain diols [e.g., 1,13-dotriacontanediol (C₃₂-diol)] (SI Discussion).Lignin monomers provide evidence for woody and nonwoody plants. This refractory biopolymer occurs in both leaves and wood, serves as a structural tissue, and accounts for up to half of the total organic carbon in modern vegetation (11). Lignin is composed of three phenolic monomer types that show distinctive distributions in woody and herbaceous plant tissues. Woody tissues from dicotyledonous trees and shrubs contain syringyl (S) and vanillyl (V) phenols (12), whereas cinnamyl (C) phenols are exclusively found in herbaceous tissues (12). The relative abundance of C versus V phenols (C/V) is widely used to distinguish between woody and herbaceous inputs to sedimentary and soil organic matter (15).Plant biomarker ¹³C/¹²C ratios (expressed as δ¹³C values) are sensitive indicators of community composition, ecosystem structure, and climate conditions (8). Most woody plants and forbs in eastern Africa use C₃ photosynthesis (6), whereas arid-adapted grasses use C₄ photosynthesis (8, 14). These two pathways discriminate differently against ¹³C during photosynthesis, resulting in characteristic δ¹³C values for leaf waxes derived from C₃ (about –36.0‰) and C₄ (–21.0‰) plants (16). Carbon isotopic abundances of phenolic monomers of lignin amplify the C₃–C₄ difference and range between ca. –34.0‰ (C₃) and –14.0‰ (C₄) in tropical ecosystems (15). Terrestrial C₃ plant δ¹³C values decrease with increased exposure to water, respired CO₂, and shade (8), with lowest values observed in moist regions with dense canopy (17). Although concentration and δ¹³C values of atmospheric CO₂ can affect C₃ plant δ¹³C values (17), this influence is not relevant to our work here, which focuses on a single time window (SI Discussion). The large differences in leaf-wax δ¹³C values between closed C₃ forest to open C₄ grassland are consistent with soil organic carbon isotope gradients across canopy-shaded ground surfaces (6) and serve as a quantitative proxy for woody cover (f_woody) in savannas (8).As is observed for nonhuman primates, hominin dietary choices were likely shaped by ecosystem characteristics over habitat scales of 1–1,000 m² (3–5). To evaluate plant distributions at this small spatial scale (9), we excavated 71 paleosol samples from close-correlated trenches across a ∼25,000-m² area that included FLK Zinjanthropus Level 22 (FLK Zinj) at Olduvai Gorge (Fig. 1). Recent excavations (18–21) at multiple trenches at four sites (FLK^NN, FLK^N, FLK, and FLK^S, Fig. 1D) exposed a traceable thin (5–50 cm), waxy green to olive-brown clay horizon developed by pedogenic alterations of playa lake margin alluvium (22). Weak stratification and irregular redox stains suggest initial soil development occurred during playa lake regression (18, 22), around 1.848 Ma (ref. 23 and SI Discussion). To date, craniodental remains from at least three hominin individuals (18–20), including preadolescent early Homo and Paranthropus boisei, were recovered from FLK Zinj. Fossils and artifacts embedded in the paleosol horizon often protrude into an overlying airfall tuff (18, 19), which suggests fossil remains were catastrophically buried in situ under volcanic ash. Rapid burial likely fostered the exceptional preservation of both macrofossils (10) and plant biomarkers across the FLK Zinj land surface.Open in a separate windowFig. 1.Location and map of FLK Zinj paleosol excavations. (A and B) Location of FLK Zinj as referenced to reconstructed depositional environments at Olduvai Gorge during the early Pleistocene (18, 22) and the modern gorge walls. The perennial lake contained shallow saline–alkaline waters that frequently flooded the surrounding playa margin (i.e., floodplain) flats. (C) Outline of FLK Zinj paleosol excavation sites used for our spatial biomarker reconstructions. (D) Concentric (5 m) gridded distribution map of FLK Zinj paleosol excavations relative to previous archaeological trenches (18–21). Major aggregate complexes (FLK^NN, FLK^N, FLK, and FLK^S) are color-coded to show excavation-site associations.Plant biomarker signatures reveal distinct types of vegetation juxtaposed across the FLK Zinj land surface (Figs. 2–4 and Fig. S1). In the northwest, FLK^NN trenches show high nC₂₃ δ¹³C values (Fig. 2B) as well as high C/V and P_aq values (Figs. 3 and ​and4A).4A). They indicate floating or submerged aquatic plants (macrophytes) in standing freshwater (13), a finding that is consistent with nearby low-temperature freshwater carbonates (tufa), interpreted to be deposited from spring waters (22). Adjacent FLK^N trenches have lower P_aq values (Fig. 4A) with occurrences of fern-derived C₃₂-diol and sedge-derived ⁿR₂₃ (Fig. 2 C and D). These biomarker distributions indicate an abrupt (around 10 m) transition from aquatic to wetland vegetation. Less than 100 m away (Fig. 1C), low nC₃₁ δ¹³C values (Fig. 2A) and low C/V and very low P_aq values (Figs. 3 and ​and4A)4A) collectively indicate dense woody cover (Fig. 4B). In the farthest southeastern (FLK^S) trenches, high C/V values and high δ¹³C values for C lignin phenols (Fig. 3) indicate open C₄ grassland.Open in a separate windowFig. 2.Spatial distributions and δ¹³C values for plant biomarkers across FLK Zinj. Measured and modeled δ¹³C values (large and smaller circles, respectively) are shown for (A) nC₃₁ from terrestrial plants, (B) nC₂₃ from (semi)aquatic plants, (C) C₃₂-diol from ferns, and (D) ⁿR₂₃ from sedges (see refs. 12 and 13 and SI Discussion). Modeled values [inverse distance-weighted (9)] account for spatial autocorrelation (15-m radius) in standing biomass (35) over scales of soil organic matter accumulation (11). Black dots represent paleosols with insufficient plant biomarker concentrations for isotopic analysis.Open in a separate windowFig. 3.Molecular and isotopic signatures for lignin phenols across FLK Zinj. Bivariate plots are shown for diagnostic lignin compositional parameters (see refs. 12 and 15 and Fig. 1C). Symbols are colored according to respective δ¹³C values for the C lignin phenol, p-coumaric acid. FLK symbols are uncolored due to insufficient p-coumaric acid concentrations for isotopic analysis. Representative lignin compositional parameters (12, 15) are shown for monocotyledonous herbaceous tissues (G), dicotyledonous herbaceous tissues (H), cryptogams (N), and dicotyledonous woody tissues (W).Open in a separate windowFig. 4.Spatial relationships shared between local plant resources and hominin remains. Measured and modeled values (large and smaller circles, respectively) are shown for (A) P_aq (13) and (B) f_woody (8). Modeled values [inverse distance-weighted (9)] account for spatial autocorrelation (15-m radius) in standing biomass (35) over scales of soil organic matter accumulation (11). (C) Kernel density map of cut-marked bones (18–21) across the FLK Zinj land surface (Fig. S4). High estimator values indicate hotspots of hominin butchery (Fig. S5). A shaded rectangle captures the area (ca. 0.68 probability mass) with highest cut-marked bone densities and is shown in A and B for reference.Open in a separate windowFig. S1.Total ion chromatograms for saturated hydrocarbons in representative paleosols at (A) FLK^NN, (B) FLK^N, (C) FLK, and (D) FLK^S. C₂₃, tricosane; C₂₅, pentacosane; C₂₉ nonacosane; C₃₁, hentriacontane.Biomarkers define a heterogeneous landscape at Olduvai and suggest an influence of local resources on hominin diets and behavior. It is recognized (2, 24–26) that early Homo species and P. boisei had similar physiological characteristics. These similarities in physical attributes suggest behavioral differences were what allowed for overlapping ranges and local coexistence (sympatry) of both hominins. For instance, differences in seasonal subsistence strategies or different behavior during periods of drought and limited food could have reduced local hominin competition and fostered diversification via niche specialization (27–29).Physical and isotopic properties of fossil teeth indicate P. boisei was more water-dependent [low enamel δ¹⁸O values (24)] and consumed larger quantities of abrasive, ¹³C-enriched foodstuffs [flat-worn surfaces (25) and high enamel δ¹³C values (26)] than coexisting early Homo species. Although ¹³C-enriched enamel is commonly attributed to consumption of C₄ grasses or meat from grazers (14), this was not likely, because P. boisei craniodental features are inconsistent with contemporary gramnivores (24, 25) or extensive uncooked flesh mastication (26). Numerous scholars have proposed the nutritious underground storage organs (USOs) of C₄ sedges were a staple of hominin diets (14, 24, 26, 27). Consistent with this suggestion, occurrences of ⁿR₂₃ attest to the presence of sedges at FLK^NN and FLK^N (Fig. 2D). However, the low δ¹³C values measured for ⁿR₂₃ at these same sites (Fig. 2D and Fig. S2) indicate C₃ photosynthesis (12, 16), a trait common in modern sedges that grow in alkaline wetlands and lakes (30) (Fig. S3). Thus, biomarker signatures support the presence of C₃ sedges in the wetland area of FLK Zinj.Open in a separate windowFig. S2.Total ion chromatogram [TIC (A)] and selected ion chromatograms for derivatized 5-n-alkylresorcinols [m/z 268 (●)] and midchain diols [m/z 369 (○)] from a representative paleosol at FLK^N. Also shown are δ¹³C values for homologous (B) 5-n-alkylresorcinols and (C) midchain diols. C₃₂-diol, dotriacontanediol; ⁿR₂₃, tricosylresorcinol.Open in a separate windowFig. S3.Summary phyogenetic consensus tree of Cyperaceae (sedges) based on nucleotide (rcbL and ETS1f) sequence data (50–54, 95, 96). Important taxonomic distinctions discussed in SI Discussion, Fern Alkyldiols are shown explicitly. Triangle-enclosed digits represent the number of additional branches at different levels of taxonomic classification. CEFA, Cypereae Eleocharideae Fuireneae Abildgaardieae; CSD, Cariceae Scirpeae Dulichieae.Alternative foodstuffs with abrasive, ¹³C-enriched biomass include seedless vascular plants (cryptogams), such as ferns and lycophytes [e.g., quillworts (27, 30)]. Ferns are widely distributed throughout eastern Africa in moist and shaded microhabitats (31) and are often found near dependable sources of drinking water (32). Today, ferns serve as a dietary resource for humans and nonhuman primates alike (27), and fiddlehead consumption is consistent with the inferred digestive physiology [salivary proteins (33)] and the microwear on molars (34) of P. boisei in eastern Africa (25, 26). Ferns were present at FLK^N, based on measurements of C₃₂-diol (Fig. 2D). Further, the high δ¹³C values measured for these compounds are consistent with significant fern consumption by P. boisei at Olduvai Gorge.Ferns and grasses were not the only plant foods present during the time window documented by FLK Zinj. Further, the exclusive reliance on a couple of dietary resources was improbable for P. boisei, because its fossils occur in diverse localities (24–26). Aquatic plants are an additional candidate substrate, as evidenced by high P_aq values at FLK^NN and FLK^N (Fig. 4A). Floating and submerged plants proliferate in wetlands throughout eastern Africa today (13, 14), and many produce nutritious leaves and rootstock all year long (27, 28). Although C₄ photosynthesis is rare among modern macrophytes (30), they can assimilate bicarbonate under alkaline conditions, which results in C₄-like isotope signatures in their biomass (30). Their leaf waxes, such as nC₂₃ (13), are both present and carry ¹³C-enriched signatures at FLK^NN and FLK^N (Fig. 2B). It is also likely that aquatic macrophytes sustained invertebrates and fish with comparably ¹³C-enriched biomass, as they do in modern systems (14), and we suggest aquatic animal foods could have been important in P. boisei diets (27, 28).Biomarkers across the FLK Zinj soil horizon resolve clear patterns in the distribution of plants and water and suggest critical resources that shaped hominin existence at Olduvai Gorge. The behavioral implications of local conditions require understanding of regional climate and biogeography (3–5, 7), because hominin species likely had home ranges much larger than the extent of excavated sites at FLK Zinj. Lake sediments at Olduvai Gorge include numerous stacked tuffs with precise radiometric age constraints (23). These tephrostratigraphic correlations (21) tie the FLK Zinj landscape horizon to published records of plant biomarkers in lake sediments that record climate cycles and catchment-scale variations in ecology. Correlative lake sediment data indicate the wet and wooded microhabitats of FLK Zinj sat within a catchment dominated by arid C₄ grassland (8). Under similarly arid conditions today, only a small fraction of landscape area (ca. 0.05) occurs within 5 km of either forest or standing freshwater (35). Given a paucity of shaded refuge and potable water in the catchment, the concentration of hominin butchery debris (18–21) exclusively within the forest microhabitat and adjacent to a freshwater wetland (Fig. 4) is notable. We suggest the spatial patterns defined by both macro- and molecular fossils reflect hominins engaged in social transport of resources (1–5), such as bringing animal carcasses and freshwater-sourced foods from surrounding grassy or wetland habitats to a wooded patch that provided both physical protection and access to water.     

Remote loading of preencapsulated drugs into stealth liposomes

Loading drugs into carriers such as liposomes can increase the therapeutic ratio by reducing drug concentrations in normal tissues and raising their concentrations in tumors. Although this strategy has proven advantageous in certain circumstances, many drugs are highly hydrophobic and nonionizable and cannot be loaded into liposomes through conventional means. We hypothesized that such drugs could be actively loaded into liposomes by encapsulating them into specially designed cyclodextrins. To test this hypothesis, two hydrophobic drugs that had failed phase II clinical trials because of excess toxicity at deliverable doses were evaluated. In both cases, the drugs could be remotely loaded into liposomes after their encapsulation (preloading) into cyclodextrins and administered to mice at higher doses and with greater efficacy than possible with the free drugs.There is currently wide interest in the development of nanoparticles for drug delivery (1–7). This area of research is particularly relevant to cancer drugs, wherein the therapeutic ratio (dose required for effectiveness to dose causing toxicity) is often low. Nanoparticles carrying drugs can increase this therapeutic ratio over that achieved with the free drug through several mechanisms. In particular, drugs delivered by nanoparticles are thought to selectively enhance the concentration of the drugs in tumors as a result of the enhanced permeability and retention (EPR) effect (8–18). The enhanced permeability results from a leaky tumor vascular system, whereas the enhanced retention results from the disorganized lymphatic system that is characteristic of malignant tumors.Much current work in this field is devoted to designing novel materials for nanoparticle generation. This new generation of nanoparticles can carry drugs—particularly those that are insoluble in aqueous medium—that are difficult to incorporate into conventional nanoparticles such as liposomes. However, the older generation of nanoparticles has a major practical advantage in that they have been extensively tested in humans and approved by regulatory agencies such as the Food and Drug Administration in the United States and the European Medicines Agency in Europe. Unfortunately, many drugs cannot be easily or effectively loaded into liposomes, thereby compromising their general use.In general, liposomal drug loading is achieved by either passive or active methods (9, 19–22). Passive loading involves dissolution of dried lipid films in aqueous solutions containing the drug of interest. This approach can only be used for water-soluble drugs, and the efficiency of loading is often low. In contrast, active loading can be extremely efficient, resulting in high intraliposomal concentrations and minimal wastage of precious chemotherapeutic agents (9, 23, 24). In active loading, drug internalization into preformed liposomes is typically driven by a transmembrane pH gradient. The pH outside the liposome allows some of the drug to exist in an unionized form, able to migrate across the lipid bilayer. Once inside the liposome, the drug becomes ionized due to the differing pH and becomes trapped there (Fig. 1A). Many reports have emphasized the dependence of liposome loading on the nature of the transmembrane pH gradient, membrane–water partitioning, internal buffering capacity, aqueous solubility of the drug, lipid composition, and other factors (25–28). As described in a recent model (28), the aqueous solubility of the drug is one of the requirements for efficient active loading. Another key element for the success of remote loading is the presence of weakly basic functional groups on the small molecule.Open in a separate windowFig. 1.Schematic representation of active loading of a liposome. (A) Remote loading of an ionizable hydrophilic drug using a transmembrane pH results in efficient incorporation. (B) A poorly soluble hydrophobic drug results in meager incorporation into preformed liposomes under similar conditions. (C) Encapsulation of a poorly soluble drug into an ionizable cyclodextrin (R = H, ionizable alkyl or aryl groups) enhances its water solubility and permits efficient liposomal loading via a pH gradient.Only a small fraction of chemotherapeutic agents possesses the features required for active loading with established techniques. Attempts at active loading of such nonionizable drugs into preformed liposomes result in poor loading efficiencies (Fig. 1B). One potential solution to this problem is the addition of weakly basic functional groups to otherwise unloadable drugs, an addition that would provide the charge necessary to drive these drugs across the pH gradient. However, covalent modification of drugs often alters their biological and chemical properties, and is not desirable in many circumstances. We therefore attempted to develop a general strategy that would allow loading of unmodified hydrophobic chemotherapeutics devoid of weakly basic functional groups. For this purpose, we used modified β-cyclodextrins to facilitate the loading of such drugs into liposomes (Fig. 1C).Cyclodextrins are a family of cyclic sugars that are commonly used to solubilize hydrophobic drugs (29–32). They possess a hydrophobic cavity and a hydrophilic surface and are known to stably encapsulate a large variety of hydrophobic organic molecules in aqueous media. Cyclodextrins bind to their cargos strongly enough to form relatively stable complexes, but allow a slow efflux of the entrapped drug and consequent steady concentrations of free drug once administered in vivo (33, 34). Cyclodextrins are nontoxic and biologically inert, and several have been approved for use in humans (35–38).In this work, we synthesized cyclodextrins with multiple weakly basic or weakly acidic functional groups on their solvent-exposed surfaces. We hypothesized that these modified cyclodextrins would still be able to encapsulate chemotherapeutic agents and that the cyclodextrin–drug complexes could then be remotely loaded into liposomes using pH gradients that exploited ionizable groups on the cyclodextrins rather than on the drugs themselves.