Geometrical manipulation of complex supramolecular tessellations by hierarchical assembly of amphiphilic platinum(II) complexes

Here we report complex supramolecular tessellations achieved by the directed self-assembly of amphiphilic platinum(II) complexes. Despite the twofold symmetry, these geometrically simple molecules exhibit complicated structural hierarchy in a columnar manner. A possible key to such an order increase is the topological transition into circular trimers, which are noncovalently interlocked by metal···metal and π–π interactions, thereby allowing for cofacial stacking in a prismatic assembly. Another key to success is to use the immiscibility of the tailored hydrophobic and hydrophilic sidechains. Their phase separation leads to the formation of columnar crystalline nanostructures homogeneously oriented on the substrate, featuring an unusual geometry analogous to a rhombitrihexagonal Archimedean tiling. Furthermore, symmetry lowering of regular motifs by design results in an orthorhombic lattice obtained by the coassembly of two different platinum(II) amphiphiles. These findings illustrate the potentials of supramolecular engineering in creating complex self-assembled architectures of soft materials.

Tessellation in two dimensions (2D) is a very old topic in geometry on how one or more shapes can be periodically arranged to fill a Euclidean plane without any gaps. Tessellation principles have been extensively applied in decorative art since the early times. In natural sciences, there has been a growing attention on creating ordered structures with increasingly complex architectures inspired by semi-regular Archimedean tilings (ATs) and quasicrystalline textures on account of their intriguing physical properties (1–5) and biological functions (6). Recent advances in this regard have been achieved in various fields of supramolecular science, including the programmable self-assembly of DNA molecules (7), coordination-driven assembly (8–10), supramolecular interfacial engineering (11–13), crystallization of organic polygons (14, 15), colloidal particle superlattices (16), and other soft-matter systems (17–20). Moreover, tessellation in 2D can overcome the topological frustration to generate complex semi- or non-regular patterns by using geometrically simple motifs. As exemplified by the self-templating assembly of spherical soft microparticles (21), a vast array of 2D micropatterns encoding non-regular tilings, such as rectangular, rhomboidal, hexagonal, and herringbone superlattices were obtained by layer-by-layer strategy at a liquid–liquid interface. Tessellation principles have also been extended to the self-assembly of giant molecules in three dimensions (3D). Superlattices with high space-group symmetry (Im3¯m, Pm3¯n, and P4₂/mnm) were reported in dendrimers and dendritic polymers by Percec and coworkers (22–24). Recently, Cheng and coworkers identified the highly ordered Frank–Kasper phases obtained from giant amphiphiles containing molecular nanoparticles (25–28). Despite such advancements made in the field of soft matter, an understanding of how structural ordering in supramolecular materials is influenced by the geometric factors of its constituent molecules has so far remained elusive.In light of these developments and the desire to explore the supramolecular systems, square-planar platinum(II) (Pt^II) polypyridine complexes may serve as an ideal candidate for model studies not only because of their intriguing spectroscopic and luminescence properties (29, 30), but also because of their propensity to form supramolecular polymers or oligomers via noncovalent Pt···Pt and π–π interactions (31–39). Although rod-shaped and lamellar structures are the most commonly observed in the self-assembly of planar Pt^II complexes (34–39), 2D-ordered nanostructures, such as the hexagonally packed columns (31, 40) and honeycomb-like networks (41–43), were recently first demonstrated by us.Herein, we report a serendipitous discovery of a C_2h-symmetric Pt^II amphiphile (Fig. 1A) that can hierarchically self-assemble into a 3D-ordered nanostructure with hexagonal geometry. Interestingly, this structurally anisotropic molecule possibly undergoes topological transition and interlocks to form its circular trimer by noncovalent Pt···Pt and π–π interactions (Fig. 1B). The resultant triangular motif is architecturally stabilized and preorganized for one-dimensional (1D) prismatic assembly (Fig. 1C). Together with the phase separation of the tailored hydrophobic and hydrophilic sidechains, an unusual and unique 3D hexagonal lattice is formed (Fig. 1D), in which the Pt centers adopt a rare rhombitrihexagonal AT-like order. Finally, the nanoarchitecture develops in a hierarchical manner on the substrate due to the homogeneous nucleation (Fig. 1E).Open in a separate windowFig. 1.Hierarchical self-assembly of Pt^II amphiphile into hexagonal ordering. (A) Space-filling (CPK) model of a C_2h-symmetric Pt^II amphiphile (1). All of the hydrogen atoms and counterions are omitted for clarity. (B) CPK representations of possible models of regular triangular, tetragonal, pentagonal, and hexagonal motifs formed with Pt···Pt and π–π stacking. These motifs possess a hydrophilic core (red) with various diameters wrapped by a hydrophobic shell comprising long alkyl chains (gray). (C) CPK representation of a 1D prismatic structure consisting of circular trimers with long-range Pt···Pt and π–π stacking. (D) CPK representation of a 3D columnar lattice constructed by the prismatic assemblies adopting a rare rhombitrihexagonal AT-like order. With the assistance of the phase separation, the hydrophobic domain serves as a discrete column associated with six prismatic neighbors. (E) Schematic representation of the nanoarchitecture with homogeneous orientation.     

Modulation of a protein-folding landscape revealed by AFM-based force spectroscopy notwithstanding instrumental limitations

Single-molecule force spectroscopy is a powerful tool for studying protein folding. Over the last decade, a key question has emerged: how are changes in intrinsic biomolecular dynamics altered by attachment to μm-scale force probes via flexible linkers? Here, we studied the folding/unfolding of α₃D using atomic force microscopy (AFM)–based force spectroscopy. α₃D offers an unusual opportunity as a prior single-molecule fluorescence resonance energy transfer (smFRET) study showed α₃D’s configurational diffusion constant within the context of Kramers theory varies with pH. The resulting pH dependence provides a test for AFM-based force spectroscopy’s ability to track intrinsic changes in protein folding dynamics. Experimentally, however, α₃D is challenging. It unfolds at low force (<15 pN) and exhibits fast-folding kinetics. We therefore used focused ion beam–modified cantilevers that combine exceptional force precision, stability, and temporal resolution to detect state occupancies as brief as 1 ms. Notably, equilibrium and nonequilibrium force spectroscopy data recapitulated the pH dependence measured using smFRET, despite differences in destabilization mechanism. We reconstructed a one-dimensional free-energy landscape from dynamic data via an inverse Weierstrass transform. At both neutral and low pH, the resulting constant-force landscapes showed minimal differences (∼0.2 to 0.5 k_BT) in transition state height. These landscapes were essentially equal to the predicted entropic barrier and symmetric. In contrast, force-dependent rates showed that the distance to the unfolding transition state increased as pH decreased and thereby contributed to the accelerated kinetics at low pH. More broadly, this precise characterization of a fast-folding, mechanically labile protein enables future AFM-based studies of subtle transitions in mechanoresponsive proteins.

Single-molecule force spectroscopy (SMFS) has been remarkably successful across broad classes of biological molecules (RNA, DNA, and proteins) (1–5). A particularly fruitful data acquisition regime probes multiple back-and-forth folding/unfolding transitions at near-equilibrium and equilibrium conditions (6–9). This methodology efficiently yields numerous transitions and therefore a wealth of kinetic data, one-dimensional (1D) free-energy landscape parameters, and even a full 1D projection of the free-energy landscape along the stretching axis (10, 11). The standard SMFS assay has the molecule of interest tethered via a flexible linker to the force probe, such as an optically trapped bead or an atomic force microscopy (AFM) cantilever (Fig. 1A). These micrometer-sized force probes are the primary measurement (x_meas) but have finite response time and are therefore coupled to, but do not precisely track, molecular dynamics (x_prot) (Fig. 1B) (12–14). Additionally, the flexible linker’s compliance modifies this coupling between the molecule and the force probe. Linkers stretched at a finite force (F) can even create an entropic barrier not present in the absence of applied force (15, 16). More generally, there is an expanding set of theoretical and experimental studies (12–30) investigating how such instrumental and assay parameters affect the underlying biomolecular dynamics and whether the measured dynamics are dominated by the instrument used to measure them.Open in a separate windowFig. 1.Probing the folding and unfolding dynamics of a globular protein by SMFS. (A) Cartoon showing a polyprotein consisting of a single copy of α₃D (blue) and two copies of NuG2 (red) stretched with an atomic force microscope. At low forces, the mechanically labile α₃D repeatedly unfolds and refolds as detected by a change in cantilever deflection. (B) A conceptual two-dimensional free-energy landscape shows the underlying protein extension (x_prot) and the experimentally measured extension (x_meas). The macroscopic force probe has finite temporal resolution, and the application of force can introduce an entropic barrier between resolved states. (C) The sum of the equilibrium folding and unfolding rates for α₃D in a strong denaturant (5 to 6 M urea) as a function of pH as determined in a prior smFRET study (37). (D) A conceptual sketch of α₃D’s 1D free-energy landscape deduced by a combination of smFRET and molecular dynamics studies based on Ref. 37. The dramatic increase in α₃D’s kinetics at low pH shown in panel C was explained as increased configurational diffusion along a smooth rather than a rough energy landscape.AFM characterization of proteins is widely used (1–5) and therefore is an important experimental regime to explore, distinct from numerous studies investigating instrumental effects on nucleic acid hairpins measured with optical traps (17, 18, 23, 24, 26, 31). Historically, limited force precision and stability coupled with the slow response of the force probe has made it challenging to perform AFM-based equilibrium and near-equilibrium studies (32) and thereby difficult to quantify the role of instrumental artifacts. Recent work using a standard gold-coated cantilever concluded that the equilibrium dynamics of the fast-folding protein gpW were dominated by the dynamics of the cantilever diffusing on a force-induced entropic barrier (29). Such results raise significant concerns about interpreting rates or landscapes measured in AFM studies of globular protein folding and thereby motivate the following question: How do variations in intrinsic protein folding dynamics manifest in AFM-based studies, particularly in an experimental regime dominated by an instrument-induced entropic barrier?Here, we address this question by directly modulating a globular protein’s underlying folding dynamics without significantly changing the height of the barrier or the free-energy difference between the states. To do so, we studied α₃D using AFM-based force spectroscopy (Fig. 1A). The dynamics and energetics of α₃D, a computationally designed, fast-folding three-helix bundle of 73 amino acids (33, 34), have been studied by traditional ensemble (33) and single-molecule fluorescence resonance energy transfer (smFRET) (35–39) assays. Equilibrium smFRET studies in chemical denaturants showed accelerated folding/unfolding kinetics as pH was reduced (35). A subsequent landmark paper (37) combined state-of-the-art smFRET and microsecond-long, all-atom molecular dynamics simulations to show that this acceleration resulted from suppression of nonnative contacts changing the local roughness of the 1D landscape (Fig. 1 C and D) rather than a change in the height or the overall shape of the barrier between states. In the context of Kramers theory (40), this roughness manifests as a change in D, the conformational diffusion coefficient along the 1D landscape. The authors concluded that most, if not all, of the 14-fold change in folding kinetics came from an increase in D. This pH-dependent change in kinetics serves as a benchmark of α₃D’s dynamics in the absence of the force probe and associated linker. In other words, we will leverage conditions known to modulate the rate of folding along the molecular coordinate (x_prot) while measuring the consequence of that change on the measured coordinate (x_meas) (Fig. 1B).While α₃D provides a conceptually attractive means to modulate intrinsic molecular dynamics, it presents significant experimental challenges. Like gpW (28, 29), α₃D unfolds at a low force (< 15 pN) by AFM standards (2, 3, 41) and exhibits even faster folding kinetics under force. Thus, spatiotemporal resolution is critical, and instrumentation limitations are expected to be even more pronounced. Force drift is also a critical issue, particularly for extended assays (>1 to 100 s) because standard gold-coated cantilevers exhibit significant force drift (42); yet, equilibrium assays of structured RNA (6) and proteins (9) are sensitive to sub-pN changes in F. We therefore used focused ion beam (FIB)–modified cantilevers (32, 43) that combine sub-pN stability over 100 s (43, 44) with a ∼13-fold improvement in spatiotemporal precision compared with the standard cantilever used in the aforementioned AFM study characterizing gpW (29). This stability in conjunction with a newly designed polyprotein construct allowed us to measure an individual α₃D unfold and fold over 5,000 times and for periods up to 1 h using both constant velocity (v) and equilibrium (v = 0) data acquisition protocols. Rates derived from both the equilibrium and dynamic data recapitulated α₃D’s pH-dependent kinetics from smFRET. However, the reconstructed 1D folding-energy landscape was consistent with the predicted entropic barrier and therefore encodes no information about α₃D’s folding landscape beyond ΔG₀, the thermodynamic stability of α₃D. Importantly, rate analysis yielded the expected asymmetric distance to the transition state from the folded and unfolded state and revealed a significant increase in the distance to the unfolding transition state as pH was lowered. These studies demonstrate that AFM-force spectroscopy can track changes in intrinsic protein dynamics with high precision, even in mechanically labile, fast-folding systems.     

A solution to a sex ratio puzzle in Melittobia wasps

The puzzling sex ratio behavior of Melittobia wasps has long posed one of the greatest questions in the field of sex allocation. Laboratory experiments have found that, in contrast to the predictions of theory and the behavior of numerous other organisms, Melittobia females do not produce fewer female-biased offspring sex ratios when more females lay eggs on a patch. We solve this puzzle by showing that, in nature, females of Melittobia australica have a sophisticated sex ratio behavior, in which their strategy also depends on whether they have dispersed from the patch where they emerged. When females have not dispersed, they lay eggs with close relatives, which keeps local mate competition high even with multiple females, and therefore, they are selected to produce consistently female-biased sex ratios. Laboratory experiments mimic these conditions. In contrast, when females disperse, they interact with nonrelatives, and thus adjust their sex ratio depending on the number of females laying eggs. Consequently, females appear to use dispersal status as an indirect cue of relatedness and whether they should adjust their sex ratio in response to the number of females laying eggs on the patch.

Sex allocation has produced many of the greatest success stories in the study of social behaviors (1–4). Time and time again, relatively simple theory has explained variation in how individuals allocate resources to male and female reproduction. Hamilton’s local mate competition (LMC) theory predicts that when n diploid females lay eggs on a patch and the offspring mate before the females disperse, the evolutionary stable proportion of male offspring (sex ratio) is (n − 1)/2n (Fig. 1) (5). A female-biased sex ratio is favored to reduce competition between sons (brothers) for mates and to provide more mates (daughters) for those sons (6–8). Consistent with this prediction, females of >40 species produce female-biased sex ratios and reduce this female bias when multiple females lay eggs on the same patch (higher n; Fig. 1) (9). The fit of data to theory is so good that the sex ratio under LMC has been exploited as a “model trait” to study the factors that can constrain “perfect adaptation” (4, 10–13).Open in a separate windowFig. 1.LMC. The sex ratio (proportion of sons) is plotted versus the number of females laying eggs on a patch. The bright green dashed line shows the LMC theory prediction for the haplodiploid species (5, 39). A more female-biased sex ratio is favored in haplodiploids because inbreeding increases the relative relatedness of mothers to their daughters (7, 32). Females of many species adjust their offspring sex ratio as predicted by theory, such as the parasitoid Nasonia vitripennis (green diamonds) (82). In contrast, the females of several Melittobia species, such as M. australica, continue to produce extremely female-biased sex ratios, irrespective of the number of females laying eggs on a patch (blue squares) (15).In stark contrast, the sex ratio behavior of Melittobia wasps has long been seen as one of the greatest problems for the field of sex allocation (3, 4, 14–21). The life cycle of Melittobia wasps matches the assumptions of Hamilton’s LMC theory (5, 15, 19, 21). Females lay eggs in the larvae or pupae of solitary wasps and bees, and then after emergence, female offspring mate with the short-winged males, who do not disperse. However, laboratory experiments on four Melittobia species have found that females lay extremely female-biased sex ratios (1 to 5% males) and that these extremely female-biased sex ratios change little with increasing number of females laying eggs on a patch (higher n; Fig. 1) (15, 17–20, 22). A number of hypotheses to explain this lack of sex ratio adjustment have been investigated and rejected, including sex ratio distorters, sex differential mortality, asymmetrical male competition, and reciprocal cooperation (15–18, 20, 22–26).We tested whether Melittobia’s unusual sex ratio behavior can be explained by females being related to the other females laying eggs on the same patch. After mating, some females disperse to find new patches, while some may stay at the natal patch to lay eggs on previously unexploited hosts (Fig. 2). If females do not disperse, they can be related to the other females laying eggs on the same host (27–31). If females laying eggs on a host are related, this increases the extent to which relatives are competing for mates and so can favor an even more female-biased sex ratio (28, 32–35). Although most parasitoid species appear unable to directly assess relatedness, dispersal behavior could provide an indirect cue of whether females are with close relatives (36–38). Consequently, we predict that when females do not disperse and so are more likely to be with closer relatives, they should maintain extremely female-biased sex ratios, even when multiple females lay eggs on a patch (28, 35).Open in a separate windowFig. 2.Host nest and dispersal manners of Melittobia. (A) Photograph of the prepupae of the leaf-cutter bee C. sculpturalis nested in a bamboo cane and (B) a diagram showing two ways that Melittobia females find new hosts. The mothers of C. sculpturalis build nursing nests with pine resin consisting of individual cells in which their offspring develop. If Melittobia wasps parasitize a host in a cell, female offspring that mate with males inside the cell find a different host on the same patch (bamboo cane) or disperse by flying to other patches.We tested whether the sex ratio of Melittobia australica can be explained by dispersal status in a natural population. We examined how the sex ratio produced by females varies with the number of females laying eggs on a patch and whether or not they have dispersed before laying eggs. To match our data to the predictions of theory, we developed a mathematical model tailored to the unique population structure of Melittobia, where dispersal can be a cue of relatedness. We then conducted a laboratory experiment to test whether Melittobia females are able to directly access the relatedness to other females and adjust their sex ratio behavior accordingly. Our results suggest that females are adjusting their sex ratio in response to both the number of females laying eggs on a patch and their relatedness to the other females. However, relatedness is assessed indirectly by whether or not they have dispersed. Consequently, the solution to the puzzling behavior reflects a more-refined sex ratio strategy.     

From the Cover: Evidence from South Africa for a protracted end-Permian extinction on land

Earth’s largest biotic crisis occurred during the Permo–Triassic Transition (PTT). On land, this event witnessed a turnover from synapsid- to archosauromorph-dominated assemblages and a restructuring of terrestrial ecosystems. However, understanding extinction patterns has been limited by a lack of high-precision fossil occurrence data to resolve events on submillion-year timescales. We analyzed a unique database of 588 fossil tetrapod specimens from South Africa’s Karoo Basin, spanning ∼4 My, and 13 stratigraphic bin intervals averaging 300,000 y each. Using sample-standardized methods, we characterized faunal assemblage dynamics during the PTT. High regional extinction rates occurred through a protracted interval of ∼1 Ma, initially co-occurring with low origination rates. This resulted in declining diversity up to the acme of extinction near the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary. Regional origination rates increased abruptly above this boundary, co-occurring with high extinction rates to drive rapid turnover and an assemblage of short-lived species symptomatic of ecosystem instability. The “disaster taxon” Lystrosaurus shows a long-term trend of increasing abundance initiated in the latest Permian. Lystrosaurus comprised 54% of all specimens by the onset of mass extinction and 70% in the extinction aftermath. This early Lystrosaurus abundance suggests its expansion was facilitated by environmental changes rather than by ecological opportunity following the extinctions of other species as commonly assumed for disaster taxa. Our findings conservatively place the Karoo extinction interval closer in time, but not coeval with, the more rapid marine event and reveal key differences between the PTT extinctions on land and in the oceans.

Mass extinctions are major perturbations of the biosphere resulting from a wide range of different causes including glaciations and sea level fall (1), large igneous provinces (2), and bolide impacts (3, 4). These events caused permanent changes to Earth’s ecosystems, altering the evolutionary trajectory of life (5). However, links between the broad causal factors of mass extinctions and the biological and ecological disturbances that lead to species extinctions have been difficult to characterize. This is because ecological disturbances unfold on timescales much shorter than the typical resolution of paleontological studies (6), particularly in the terrestrial record (6–8). Coarse-resolution studies have demonstrated key mass extinction phenomena including high extinction rates and lineage turnover (7, 9), changes in species richness (10), ecosystem instability (11), and the occurrence of disaster taxa (12). However, finer time resolutions are central to determining the association and relative timings of these effects, their potential causal factors, and their interrelationships. Achieving these goals represents a key advance in understanding the ecological mechanisms of mass extinctions.The end-Permian mass extinction (ca. 251.9 Ma) was Earth’s largest biotic crisis as measured by taxon last occurrences (13–15). Large outpourings from Siberian Trap volcanism (2) are the likely trigger of calamitous climatic changes, including a runaway greenhouse effect and ocean acidification, which had profound consequences for life on land and in the oceans (16–18). An estimated 81% of marine species (19) and 89% of tetrapod genera became extinct as established Permian ecosystems gave way to those of the Triassic. In the ocean, this included the complete extinction of reef-forming tabulate and rugose corals (20, 21) and significant losses in previously diverse ammonoid, brachiopod, and crinoid families (22). On land, many nonmammalian synapsids became extinct (16), and the glossopterid-dominated floras of Gondwana also disappeared (23). Stratigraphic sequences document a global “coral gap” and “coal gap” (24, 25), suggesting reef and forest ecosystems were rare or absent for up to 5 My after the event (26). Continuous fossil-bearing deposits documenting patterns of turnover across the Permian–Triassic transition (PTT) on land (27) and in the oceans (28) are geographically widespread (29, 30), including marine and continental successions that are known from China (31, 32) and India (33). Continental successions are known from Russia (34), Australia (35), Antarctica (36), and South Africa’s Karoo Basin (Fig. 1 and 37–40), the latter providing arguably the most densely sampled and taxonomically scrutinized (41–43) continental record of the PTT. The main extinction has been proposed to occur at the boundary between two biostratigraphic zones with distinctive faunal assemblages, the Daptocephalus and Lystrosaurus declivis assemblage zones (Fig. 1), which marks the traditional placement of the Permian–Triassic geologic boundary [(37) but see ref. 44]. Considerable research has attempted to understand the anatomy of the PTT in South Africa (38, 39, 45–52) and to place it in the context of biodiversity changes across southern Gondwana (53, 54) and globally (29, 31, 32, 44, 47, 55).Open in a separate windowFig. 1.Map of South Africa depicting the distribution of the four tetrapod fossil assemblage zones (Cistecephalus, Daptocephalus, Lystrosaurus declivis, Cynognathus) and our two study sites where fossils were collected in this study (sites A and B). Regional lithostratigraphy and biostratigraphy within the study interval are shown alongside isotope dilution–thermal ionization mass spectrometry dates retrieved by Rubidge et al., Botha et al., and Gastaldo et al. (37, 44, 80). The traditional (dashed red line) and associated PTB hypotheses for the Karoo Basin (37, 44) are also shown. Although traditionally associated with the PTB, the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary is defined by first appearances of co-occurring tetrapod assemblages, so its position relative to the three PTB hypotheses is unchanged. The Ripplemead member (*) has yet to be formalized by the South African Committee for Stratigraphy.Decades of research have demonstrated the richness of South Africa’s Karoo Basin fossil record, resulting in hundreds of stratigraphically well-documented tetrapod fossils across the PTT (37, 39, 56). This wealth of data has been used qualitatively to identify three extinction phases and an apparent early postextinction recovery phase (39, 45, 51). Furthermore, studies of Karoo community structure and function have elucidated the potential role of the extinction and subsequent recovery in breaking the incumbency of previously dominant clades, including synapsids (11, 57). Nevertheless, understanding patterns of faunal turnover and recovery during the PTT has been limited by the scarcity of quantitative investigations. Previous quantitative studies used coarsely sampled data (i.e., assemblage zone scale, 2 to 3 Ma time intervals) to identify low species richness immediately after the main extinction, potentially associated with multiple “boom and bust” cycles of primary productivity based on δ¹³C variation during the first 5 My of the Triassic (41, 58). However, many details of faunal dynamics in this interval remain unknown. Here, we investigate the dynamics of this major tetrapod extinction at an unprecedented time resolution (on the order of hundreds of thousands of years), using sample-standardized methods to quantify multiple aspects of regional change across the Cistecephalus, Daptocephalus, and Lystrosaurus declivis assemblage zones.     

Stable metal anodes enabled by a labile organic molecule bonded to a reduced graphene oxide aerogel

Metallic anodes (lithium, sodium, and zinc) are attractive for rechargeable battery technologies but are plagued by an unfavorable metal–electrolyte interface that leads to nonuniform metal deposition and an unstable solid–electrolyte interphase (SEI). Here we report the use of electrochemically labile molecules to regulate the electrochemical interface and guide even lithium deposition and a stable SEI. The molecule, benzenesulfonyl fluoride, was bonded to the surface of a reduced graphene oxide aerogel. During metal deposition, this labile molecule not only generates a metal-coordinating benzenesulfonate anion that guides homogeneous metal deposition but also contributes lithium fluoride to the SEI to improve Li surface passivation. Consequently, high-efficiency lithium deposition with a low nucleation overpotential was achieved at a high current density of 6.0 mA cm⁻². A Li|LiCoO₂ cell had a capacity retention of 85.3% after 400 cycles, and the cell also tolerated low-temperature (−10 °C) operation without additional capacity fading. This strategy was applied to sodium and zinc anodes as well.

Rechargeable batteries based on metal anodes including lithium (Li), sodium (Na), and zinc (Zn) show great promise in achieving high energy density (1–3). Unfortunately, the electrochemical interface of the metal anodes is not favorable for metal deposition. Metal nucleation is inhomogeneous at the surface, leading to the growth of metal dendrites (4–7) and the formation of an unstable solid–electrolyte interphase (SEI) that is incapable of protecting metals from the side reactions with the electrolyte (8–12).Substantial efforts have been devoted to stabilizing the interface of metal anodes, especially for Li metal. These include the design of artificial protective layers (13–17), alternative electrolytes (18–24), and sacrificial additives (25–30) to stabilize the metal–electrolyte interface, the development of mechanically robust coatings (31–34) to block Li dendrite growth, and the use of structured scaffolds to host dendrite-free Li deposition by reducing local current densities (35–43). However, the performance of metal anodes remains poor under high-current or low-temperature conditions. This is because the inhomogeneous Li nucleation and unstable SEI problems have not been well addressed, and these problems at the interface are even exacerbated under critical operating conditions, especially high-current densities and low temperatures (5, 6, 44).Toward this end, we report a simple molecular approach for regulating the electrochemical interface of metal anodes, which enables even Li deposition and stable SEI formation in a conventional electrolyte. This was realized by bonding a labile organic molecule, benzenesulfonyl fluoride (BSF), to a reduced graphene oxide (rGO) aerogel surface as the Li anode host (Fig. 1A). During Li deposition, BSF molecules electrochemically decompose at the interface and generate benzenesulfonate anions bonded to the rGO aerogel (Fig. 1B). The conjugated anions have a strong binding affinity for Li, serving as lithiophilic sites on the rGO surface to synergistically induce homogeneous Li nucleation of Li on the rGO surface. At the same time, BSF molecules contribute LiF to the SEI layer, which facilitates Li surface passivation (Fig. 1C). As a result, high-efficiency (99.2%) Li deposition was achieved at a Li deposition amount of 6.0 mAh cm⁻² and a current density of 6.0 mA cm⁻²; the barrier to Li nucleation was markedly reduced, as evidenced by the low nucleation overpotentials at high-current density (6.0 mA cm⁻²) or at a low temperature (−10 °C). A 400-cycle life with a capacity retention of 83.6% was achieved for a Li|LiCoO₂ (LCO) cell in a conventional carbonate electrolyte. Moreover, with the organic molecule-tuned interface, the Li|LCO cell can be stably cycled at a low operating temperature (−10 °C). This approach was applied to Na and Zn metal anodes as well.Open in a separate windowFig. 1.Illustration of a stable interface for Li deposition using a labile organic molecule, benzenesulfonyl fluoride (BSF). (A) Covalently bonded BSF on the rGO aerogel surface. (B) In situ generation of a lithiophilic conjugated anion (benzenesulfonate) and LiF on the surface during Li deposition. (C) Li nucleation preferentially occurs at the conjugated anion sites owing to the strong Li binding affinity, which leads to uniform Li deposition. In addition, the LiF that is formed is in the SEI layer and passivates the Li surface.     

Elementary mechanisms of calmodulin regulation of NaV1.5 producing divergent arrhythmogenic phenotypes

In cardiomyocytes, Na_V1.5 channels mediate initiation and fast propagation of action potentials. The Ca²⁺-binding protein calmodulin (CaM) serves as a de facto subunit of Na_V1.5. Genetic studies and atomic structures suggest that this interaction is pathophysiologically critical, as human mutations within the Na_V1.5 carboxy-terminus that disrupt CaM binding are linked to distinct forms of life-threatening arrhythmias, including long QT syndrome 3, a “gain-of-function” defect, and Brugada syndrome, a “loss-of-function” phenotype. Yet, how a common disruption in CaM binding engenders divergent effects on Na_V1.5 gating is not fully understood, though vital for elucidating arrhythmogenic mechanisms and for developing new therapies. Here, using extensive single-channel analysis, we find that the disruption of Ca²⁺-free CaM preassociation with Na_V1.5 exerts two disparate effects: 1) a decrease in the peak open probability and 2) an increase in persistent Na_V openings. Mechanistically, these effects arise from a CaM-dependent switch in the Na_V inactivation mechanism. Specifically, CaM-bound channels preferentially inactivate from the open state, while those devoid of CaM exhibit enhanced closed-state inactivation. Further enriching this scheme, for certain mutant Na_V1.5, local Ca²⁺ fluctuations elicit a rapid recruitment of CaM that reverses the increase in persistent Na current, a factor that may promote beat-to-beat variability in late Na current. In all, these findings identify the elementary mechanism of CaM regulation of Na_V1.5 and, in so doing, unravel a noncanonical role for CaM in tuning ion channel gating. Furthermore, our results furnish an in-depth molecular framework for understanding complex arrhythmogenic phenotypes of Na_V1.5 channelopathies.

Voltage-gated sodium channels (Na_V) are responsible for the initiation and spatial propagation of action potentials (AP) in excitable cells (1, 2). Na_V channels undergo rapid activation that underlie the AP upstroke while ensuing inactivation permits AP repolarization. The Na_V1.5 channel constitutes the predominant isoform in cardiomyocytes, whose pore-forming α-subunit is encoded by the SCN5A gene. Na_V1.5 dysfunction underlies diverse forms of cardiac disease including cardiomyopathies, arrhythmias, and sudden death (3–6). Human mutations in Na_V1.5 are associated with two forms of inherited arrhythmias–congenital long QT syndrome 3 (LQTS3) and Brugada syndrome (BrS) (7). LQTS3 stems from delayed or incomplete inactivation of Na_V1.5 that causes persistent Na influx that prolongs AP repolarization—a “gain-of-function” phenotype (7–9). BrS predisposes patients to sudden death and is associated with a reduction in the peak Na current that may slow cardiac conduction or cause region-specific repolarization differences—a “loss-of-function” phenotype (10, 11). Genetic studies have identified an expanding array of mutations in multiple Na_V1.5 domains, including the channel carboxy-terminus (CT) that is a hotspot for mutations linked to both LQTS3 and BrS (12, 13). This domain interacts with the Ca²⁺-binding protein calmodulin (CaM), suggesting that altered CaM regulation of Na_V1.5 may be a common pathophysiological mechanism (12, 14–16). More broadly, human mutations in the homologous regions of neuronal Na_V1.1 (17, 18), Na_V1.2 (19, 20), and Na_V1.6 (21) as well as skeletal muscle Na_V1.4 (22) are linked to varied clinical phenotypes including epilepsy, autism spectrum disorder, neurodevelopmental delay, and myotonia (23). Taken together, a common Na_V mechanistic deficit—defective CaM regulation—may underlie these diverse diseases.CaM regulation of Na_V channels is complex, isoform specific, and mediated by multiple interfaces within the channel (14–16). The Na_V CT consists of a dual vestigial EF hand segment and a canonical CaM-binding “IQ” (isoleucine–glutamine) domain (24, 25) (Fig. 1A). The IQ domain of nearly all Na_V channels binds to both Ca²⁺-free CaM (apoCaM) and Ca²⁺/CaM, similar to Ca_V channels (26–31). As CaM is typically a Ca²⁺-dependent regulator, much attention has been focused on elucidating Ca²⁺-dependent changes in Na_V gating. For skeletal muscle Na_V1.4, transient elevation in cytosolic Ca²⁺ causes a dynamic reduction in the peak current, a process reminiscent of Ca²⁺/CaM-dependent inactivation of Ca_V channels (32). Cardiac Na_V1.5 by comparison exhibits no dynamic effect of Ca²⁺ on the peak current (32–34). Instead, sustained Ca²⁺ elevation has been shown to elicit a depolarizing shift in Na_V1.5 steady-state inactivation (SSI or h_∞), although the magnitude and the presence of a shift have been debated (32, 35). Additional CaM-binding sites have been identified in the channel amino terminus domain (36) and the III-IV linker near the isoleucine, phenylalanine, and methionine (IFM) motif that is well recognized for its role in fast inactivation (35, 37). However, recent cryogenic electron microscopy structures, biochemical, and functional analyses suggest that both the III-IV linker and the Domain IV voltage-sensing domain might instead interact with the channel CT in a state-dependent manner (38–43).Open in a separate windowFig. 1.Absence of dynamic Ca²⁺/CaM effects on WT Na_V1.5 SSI. (A, Left) Structure of Na_V1.5 transmembrane domain (6UZ3) (70) juxtaposed with that of Na_V1.5 CT–apoCaM complex (4OVN) (28). (Right) Arrhythmia-linked CT mutations highlighted in Na_V1.5 CT–apoCaM structure (LQTS3, blue; BrS, magenta; mixed syndrome, purple). (B) Dynamic Ca²⁺-dependent changes in Na_V1.5 SSI probed using Ca²⁺ photouncaging. Na currents specifying h_∞ at ∼100 nM (Left) and ∼4 μM Ca²⁺ step (Right). (C) Population data for Na_V1.5 SSI under low (black, Left) versus high (red, Right) intracellular Ca²⁺ reveal no differences (P = 0.55, paired t test). Dots and bars are mean ± SEM (n = 8 cells). (D) FRET two-hybrid analysis of Cerulean-tagged apoCaM interaction with various Venus-tagged Na_V1.5 CT (WT, black; IQ/AA, red; S[1904]L, blue). Each dot is FRET efficiency measured from a single cell. Solid line fits show 1:1 binding isotherm.Beyond Ca²⁺-dependent effects, the loss of apoCaM binding to the Na_V1.5 IQ domain increases persistent current (34, 44), suggesting that apoCaM itself may be pathophysiologically relevant. Indeed, Na_V1.5 mutations in the apoCaM-binding interface are associated with LQTS3 and atrial fibrillation (7), as well as a loss-of-function BrS phenotype and a mixed-syndrome phenotype whereby some patients present with BrS while others with LQTS3 (Fig. 1A) (13, 45). How alterations in CaM binding paradoxically elicits both gain-of-function and loss-of-function effects is not fully understood, though important to delineate pathophysiological mechanisms and for personalized therapies.Here, using single- and multichannel recordings, we show that apoCaM binding elicits two distinct effects on Na_V1.5 gating: 1) an increase in the peak channel open probability (P_O/peak) and 2) a reduction in the normalized persistent channel open probability (R_persist), consistent with previous studies (34, 44). The two effects may explain how mixed-syndrome mutations in the Na_V1.5 CT produce either BrS or LQTS3 phenotypes. On one hand, the loss of apoCaM association may diminish P_O/peak and induce BrS by shunting cardiac AP. On the other hand, increased R_persist may prevent normal AP repolarization, resulting in LQTS3. Analysis of elementary mechanisms suggests that these changes relate to a switch in the state dependence of channel inactivation. Furthermore, dynamic changes in Ca²⁺ can inhibit persistent current for certain mutant Na_V1.5 owing to enhanced Ca²⁺/CaM binding that occurs over the timescale of a cardiac AP. This effect may result in beat-to-beat variability in persistent Na current for some mutations. In all, these findings explain how a common deficit in CaM binding can contribute to distinct arrhythmogenic mechanisms.     

Developmental influence on evolutionary rates and the origin of placental mammal tooth complexity

Development has often been viewed as a constraining force on morphological adaptation, but its precise influence, especially on evolutionary rates, is poorly understood. Placental mammals provide a classic example of adaptive radiation, but the debate around rate and drivers of early placental evolution remains contentious. A hallmark of early dental evolution in many placental lineages was a transition from a triangular upper molar to a more complex upper molar with a rectangular cusp pattern better specialized for crushing. To examine how development influenced this transition, we simulated dental evolution on “landscapes” built from different parameters of a computational model of tooth morphogenesis. Among the parameters examined, we find that increases in the number of enamel knots, the developmental precursors of the tooth cusps, were primarily influenced by increased self-regulation of the molecular activator (activation), whereas the pattern of knots resulted from changes in both activation and biases in tooth bud growth. In simulations, increased activation facilitated accelerated evolutionary increases in knot number, creating a lateral knot arrangement that evolved at least ten times on placental upper molars. Relatively small increases in activation, superimposed on an ancestral tritubercular molar growth pattern, could recreate key changes leading to a rectangular upper molar cusp pattern. Tinkering with tooth bud geometry varied the way cusps initiated along the posterolingual molar margin, suggesting that small spatial variations in ancestral molar growth may have influenced how placental lineages acquired a hypocone cusp. We suggest that development could have enabled relatively fast higher-level divergence of the placental molar dentition.

Whether developmental processes bias or constrain morphological adaptation is a long-standing question in evolutionary biology (1–4). Many of the distinctive features of a species derive from pattern formation processes that establish the position and number of anatomical structures (5). If developmental processes like pattern formation are biased toward generating only particular kinds of variation, adaptive radiations may often be directed along developmental–genetic “lines of least resistance” (2, 4, 6, 7). Generally, the evolutionary consequences of this developmental bias have been considered largely in terms of how it might influence the pattern of character evolution (e.g., refs. 1, 2, 8–10). But development could also influence evolutionary rates by controlling how much variation is accessible to natural selection in a given generation (11).For mammals, the dentition is often the only morphological system linking living and extinct species (12). Correspondingly, tooth morphology plays a crucial role in elucidating evolutionary relationships, time calibrating phylogenetic trees, and reconstructing adaptive responses to past environmental change (e.g., refs. 13–15). One of the most pervasive features of dental evolution among mammals is an increase in the complexity of the tooth occlusal surface, primarily through the addition of new tooth cusps (16, 17). These increases in tooth complexity are functionally and ecologically significant because they enable more efficient mechanical breakdown of lower-quality foods like plant leaves (18).Placental mammals are the most diverse extant mammalian group, comprising more than 6,000 living species spread across 19 extant orders, and this taxonomic diversity is reflected in their range of tooth shapes and dietary ecologies (12). Many extant placental orders, especially those with omnivorous or herbivorous ecologies (e.g., artiodactyls, proboscideans, rodents, and primates), convergently evolved a rectangular upper molar cusp pattern from a placental ancestor with a more triangular cusp pattern (19–21). This resulted from separate additions in each lineage of a novel posterolingual cusp, the "hypocone'''' [sensu (19)], to the tritubercular upper molar (Fig. 1), either through modification of a posterolingual cingulum (“true” hypocone) or another posterolingual structure, like a metaconule (pseudohypocone) (19). The fossil record suggests that many of the basic steps in the origin of this rectangular cusp pattern occurred during an enigmatic early diversification window associated with the divergence and early radiation of several placental orders (20, 21; Fig. 1). However, there remains debate about the rate and pattern of early placental divergence (22–24). On the one hand, most molecular phylogenies suggest that higher-level placental divergence occurred largely during the Late Cretaceous (25, 26), whereas other molecular phylogenies and paleontological analyses suggest more rapid divergence near the Cretaceous–Paleogene (K–Pg) boundary (21, 24, 27–29). Most studies agree that ecological opportunity created in the aftermath of the K–Pg extinction probably played an important role in ecomorphological diversification within the placental orders (30, 31). But exactly how early placentals acquired the innovations needed to capitalize on ecological opportunity remains unclear. Dental innovations, especially those which facilitated increases in tooth complexity, may have been important because they would have promoted expansion into plant-based dietary ecologies left largely vacant after the K–Pg extinction event (32).Open in a separate windowFig. 1.Placental mammal lineages separately evolved complex upper molar teeth with a rectangular cusp pattern composed of two lateral pairs of cusps from a common ancestor with a simpler, triangular cusp pattern. Many early relatives of the extant placental orders, such as Eritherium, possessed a hypocone cusp and a more rectangular primary cusp pattern. Examples of complex upper molars are the following: Proboscidea, the gomphothere Anancus; Rodentia, the wood mouse Apodemus; and Artiodactyla, the suid Nyanzachoerus.Mammalian tooth cusps form primarily during the “cap” and “bell” stage of dental development, when signaling centers called enamel knots establish the future sites of cusp formation within the inner dental epithelium (33, 34). The enamel knots secrete molecules that promote proliferation and changes in cell–cell adhesion, which facilitates invagination of the dental epithelium into an underlying layer of mesenchymal cells (34, 35). Although a range of genes are involved in tooth cusp patterning (36–38), the basic dynamics can be effectively modeled using reaction–diffusion models with just three diffusible morphogens: an activator, an inhibitor, and a growth factor (39–41). Candidate activator genes in mammalian tooth development include Bmp4, Activin A, Fgf20, and Wnt genes, whereas potential inhibitors include Shh and Sostdc, and Fgf4 and Bmp2 have been hypothesized to act as growth factors (38, 40–43). In computer models of tooth development, activator molecules up-regulated in the underlying mesenchyme stimulate differentiation of overlying epithelium into nondividing enamel knot cells. These in turn secrete molecules that inhibit further differentiation of epithelium into knot cells, while also promoting cell proliferation that creates the topographic relief of the cusp (40). Although many molecular, cellular, and physical processes have the potential to influence cusp formation, and thereby tooth complexity (35, 37), parameters that control the strength and conductance of the activator and inhibitor signals, the core components of the reaction–diffusion cusp patterning mechanism (39, 40) are likely to be especially important.Here, we integrate a previous computer model of tooth morphogenesis called ToothMaker (41), with simulations of trait evolution and data from the fossil record (Fig. 2), to examine the developmental origins of tooth complexity in placental mammals. Specifically, we ask the following: 1) What developmental processes can influence how many cusps form? 2) How might these developmental processes influence the evolution of tooth cusp number, especially rates? And 3) what developmental changes may have been important in the origins of the fourth upper molar cusp, the hypocone, in placental mammal evolution?Open in a separate windowFig. 2.Workflow for simulations of tooth complexity evolution. (A) Tooth shape is varied for five signaling and growth parameters in ToothMaker. (B) From an ancestral state, each parameter is varied in 2.5% increments up to a maximum of ± 50% of the ancestral state. (C) Tooth complexity and enamel knot (EK) pattern were quantified for each parameter combination. Tooth complexity was measured using cusp number/EK number and OPC. ToothMaker and placental upper second molars were classified into categories based on EK/cusp pattern. (D) The parameter space was populated with pattern and tooth complexity datums to build a developmental landscape. (E) Tooth complexity evolution was simulated on each developmental landscape. (F) Resulting diversity and pattern of tooth complexity was compared with placental mammal molar diversity.     

High-throughput developability assays enable library-scale identification of producible protein scaffold variants

Proteins require high developability—quantified by expression, solubility, and stability—for robust utility as therapeutics, diagnostics, and in other biotechnological applications. Measuring traditional developability metrics is low throughput in nature, often slowing the developmental pipeline. We evaluated the ability of 10 variations of three high-throughput developability assays to predict the bacterial recombinant expression of paratope variants of the protein scaffold Gp2. Enabled by a phenotype/genotype linkage, assay performance for 10⁵ variants was calculated via deep sequencing of populations sorted by proxied developability. We identified the most informative assay combination via cross-validation accuracy and correlation feature selection and demonstrated the ability of machine learning models to exploit nonlinear mutual information to increase the assays’ predictive utility. We trained a random forest model that predicts expression from assay performance that is 35% closer to the experimental variance and trains 80% more efficiently than a model predicting from sequence information alone. Utilizing the predicted expression, we performed a site-wise analysis and predicted mutations consistent with enhanced developability. The validated assays offer the ability to identify developable proteins at unprecedented scales, reducing the bottleneck of protein commercialization.

A common constraint across diagnostic, therapeutic, and industrial proteins is the ability to manufacture, store, and use intact and active molecules. These protein properties, collectively termed developability, are often associated to quantitative metrics such as recombinant yield, stability (chemical, thermal, and proteolytic), and solubility (1–5). Despite this universal importance, developability studies are performed late in the commercialization pipeline (2, 4) and limited by traditional experimental capacity (6). This is problematic because 1) proteins with poor developability limit practical assay capacity for measuring primary function, 2) optimal developability is often not observed with proteins originally found in alternative formats [such as display or two-hybrid technologies (7)], and 3) engineering efforts are limited by the large gap between observation size (∼10²) and theoretical mutational diversity (∼10²⁰). Thus, efficient methods to measure developability would alleviate a significant bottleneck in the lead selection process and accelerate protein discovery and engineering.Prior advances to determine developability have focused on calculating hypothesized proxy metrics from existing sequence and structural data or developing material- and time-efficient experiments. Computational sequence-developability models based on experimental antibody data have predicted posttranslational modifications (8, 9), solubility (10, 11), viscosity (12), and overall developability (13). Structural approaches have informed stability (14) and solubility (10, 15). However, many in silico models require an experimentally solved structure or suffer from computational structure prediction inaccuracies (16). Additionally, limited developability information allows for limited predictive model accuracy (17). In vitro methods have identified several experimental protocols to mimic practical developability requirements [e.g., affinity-capture self-interaction nanoparticle spectroscopy (18) and chemical precipitation (19) as metrics for solubility]. However, traditional developability quantification requires significant amounts of purified protein. Noted in both fronts are numerous in silico and/or in vitro metrics to fully quantify developability (1, 5).We sought a protein variant library that would benefit from isolation of proteins with increased developability and demonstrate the broad applicability of the process. Antibodies and other binding scaffolds, comprising a conserved framework and diversified paratope residues, are effective molecular targeting agents (20–24). While significant progress has been achieved with regards to identifying paratopes for optimal binding strength and specificity (25, 26), isolating highly developable variants remains plagued. One particular protein scaffold, Gp2, has been evolved into specific binding variants toward multiple targets (27–29). Continued study improved charge distribution (30), hydrophobicity (31), and stability (28). While these studies have suggested improvements for future framework and paratope residues (including a disulfide-stabilized loop), a poor developability distribution is still observed (32) (Fig. 1 A and B). Assuming the randomized paratope library will lack similar primary functionality, the Gp2 library will simulate the universal applicability of the proposed high-throughput (HT) developability assays.Open in a separate windowFig. 1.HT assays were evaluated for the ability to identify protein scaffold variants with increased developability. (A and B) Gp2 variant expression, commonly measured via low-throughput techniques such as the dot blot shown, highlights the rarity of ideal developability. (C and D) The HT on-yeast protease assay measures the stability of the POI by proteolytic extent. (E and F) The HT split-GFP assay measures POI expression via recombination of a genetically fused GFP fragment. (G and H) The HT split β-lactamase assay measures the POI stability by observing the change in cell-growth rates when grown at various antibiotic concentrations. (I and J) Assay scores, assigned to each unique sequence via deep sequencing, were evaluated by predicting expression (Fig. 3). (K and L) HT assay capacity enables large-scale developability evaluation and can be used to identify beneficial mutations (Fig. 4).We sought HT assays that allow protein developability differentiation via cellular properties to improve throughput. Variations of three primary assays were examined: 1) on-yeast stability (Fig. 1 C and D)—previously validated to improve the stability of de novo proteins (33), antimicrobial lysins (34), and immune proteins (35)—measures proteolytic cleavage of the protein of interest (POI) on the yeast cell surface via fluorescence-activated cell sorting (FACS). We extend the assay by performing the proteolysis at various denaturing combinations to determine if different stability attributes (thermal, chemical, and protease specificity) can be resolved; 2) Split green fluorescent protein (GFP, Fig. 1 E and F)—previously used to determine soluble protein concentrations (36)—measures the assembled GFP fluorescence emerging from a 16–amino acid fragment (GFP₁₁) fused to the POI after recombining with the separably expressed GFP_1-10. We extend the assay by utilizing FACS to separate cells with differential POI expression to increase throughput over the plate-based assay; and 3) Split β-lactamase (Fig. 1 G and H)—previously used to improve thermodynamic stability (37) and solubility (38)—measures cell growth inhibition via ampicillin to determine functional lactamase activity achieved from reconstitution of two enzyme fragments flanking the POI. We expand assay capacity by deep sequencing populations grown at various antibiotic concentrations to relate change in cell frequency to functional enzyme concentration.In this paper, we determined the HT assays’ abilities to predict Gp2 variant developability. We deep sequenced the stratified populations and calculated assay scores (correlating to hypothesized developability) for ∼10⁵ Gp2 variants (Fig. 1I). We then converted the assay scores into a traditional developability metric by building a model that predicts recombinant yield (Fig. 1J). The assays’ capacity enabled yield evaluations for >100-fold traditional assay capacity (Fig. 1K, compared to Fig. 1B) and provide an introductory analysis of factors driving protein developability by observing beneficial mutations via predicted developable proteins (Fig. 1L).     

The number of catalytic cycles in an enzyme’s lifetime and why it matters to metabolic engineering

Metabolic engineering uses enzymes as parts to build biosystems for specified tasks. Although a part’s working life and failure modes are key engineering performance indicators, this is not yet so in metabolic engineering because it is not known how long enzymes remain functional in vivo or whether cumulative deterioration (wear-out), sudden random failure, or other causes drive replacement. Consequently, enzymes cannot be engineered to extend life and cut the high energy costs of replacement. Guided by catalyst engineering, we adopted catalytic cycles until replacement (CCR) as a metric for enzyme functional life span in vivo. CCR is the number of catalytic cycles that an enzyme mediates in vivo before failure or replacement, i.e., metabolic flux rate/protein turnover rate. We used estimated fluxes and measured protein turnover rates to calculate CCRs for ∼100–200 enzymes each from Lactococcus lactis, yeast, and Arabidopsis. CCRs in these organisms had similar ranges (<10³ to >10⁷) but different median values (3–4 × 10⁴ in L. lactis and yeast versus 4 × 10⁵ in Arabidopsis). In all organisms, enzymes whose substrates, products, or mechanisms can attack reactive amino acid residues had significantly lower median CCR values than other enzymes. Taken with literature on mechanism-based inactivation, the latter finding supports the proposal that 1) random active-site damage by reaction chemistry is an important cause of enzyme failure, and 2) reactive noncatalytic residues in the active-site region are likely contributors to damage susceptibility. Enzyme engineering to raise CCRs and lower replacement costs may thus be both beneficial and feasible.

As the synthetic biology revolution brings engineering principles and practices into the life sciences, biomolecules are being rethought as component parts that are used to build new biosystems and improve existing ones (1–3). Enzymes—the working parts of metabolic systems—are targets for this rethinking and are increasingly being repurposed by rational design and directed evolution (4).Substrate specificity, catalytic efficiency, and expression level are common performance specifications for enzyme parts in metabolic engineering, but life span is not, despite its centrality in other engineering fields. Knowing an engineering component’s life span (how long it lasts in service) is critical to preventing system failures and optimizing maintenance schedules (5). Failure metrics such as “mean time to failure” (6) are consequently used widely in engineering, which distinguishes three types of failures: early, wear-out, and random or stochastic. All three have counterparts in enzymes operating in vivo (Fig. 1A) (7–18), but wear-out and random failures (Fig. 1A, red font) are most relevant to length of working life.Open in a separate windowFig. 1.The engineering concept of component failure and its application to enzymes in vivo. (A) The types of failure in manufactured components and their counterparts in enzymes operating in vivo. (B) Schematic representation of the time dependence of the hazard rate and the cumulative probability (increasing color density) that an individual component will have failed.In manufactured systems, wear-out failures are caused by cumulative deterioration processes or by use-dependent wear (Fig. 1A). Like all proteins, enzymes are subject to cumulative deterioration from oxidation, racemization, or other chemical events (“protein fatigue”) that can affect any part of the molecule and degrade its function (9–11). However, use-dependent wear-out has no equivalent in enzymes, i.e., enzyme performance is not progressively degraded by operation of the catalytic cycle in the way a bearing is worn down a little each time it turns (Fig. 1A). Rather, a random catalytic misfire or a chemical attack by a substrate or product on a vulnerable residue in the active-site region can instantly inactivate an enzyme, whatever its age (14–18). Such failures thus have a constant hazard rate and are random or stochastic, like the abrupt failure of a transistor due to a current surge (Fig. 1A).Although the hazard of random failure does not depend on a part’s age, the cumulative probability that any individual part will experience a random failure increases with time (Fig. 1B). Given long enough, certain types of enzyme molecule may thus be doomed to have a terminal, catalysis-related accident. Such self-inflicted inactivation processes are important considerations for industrial enzymes (i.e., enzymes used ex vivo as reagents) and the number of catalytic cycles that each enzyme molecule carries out in its lifetime—often called “total turnover number”—is a key industrial performance criterion (19–21).The number of catalytic cycles mediated before self-inactivation could also be key to in vivo enzyme performance. Recent proteomic evidence points to damage from the reaction catalyzed as a major mode of enzyme failure and to the possibility that some reactions do more damage than others. Thus, in the bacterium Lactococcus lactis, a fivefold increase in growth rate was accompanied by a sevenfold increase in protein turnover rate (22). This near proportionality implies that L. lactis enzymes catalyze a similar number of reactions in their lifetimes, whatever the growth rate. This fits with reaction-related damage as a cause of failure: The faster the growth, the more flux through reactions, the more damage to enzymes, and the sooner enzymes fail. Similarly, protein turnover in yeast was faster when enzymes were in active use (23). Furthermore, in L. lactis, yeast, and Arabidopsis, the fastest turning-over metabolic enzymes include many with reactive substrates, products, or intermediates (SI Appendix, Table S1) (22–24), i.e., with a high risk of spontaneous chemical damage to the active site.The rates at which enzyme proteins are degraded and resynthesized are critical to the cellular energy economy because such turnover can consume about half the maintenance energy budget in microbes and plants (22, 25–27). High enzyme protein turnover rates therefore potentially reduce the productivity of biosystems ranging from microbial fermentations to crops (26, 28, 29). Consistent with such reduction, fast protein turnover is associated with low biomass yield in yeast (27) and with low growth rate in Arabidopsis (30). Also, slowing the turnover of abundant, fast-turnover enzymes is predicted to substantially increase growth rate and biomass yield in plants (26, 31) and other organisms (32).Rational design or directed evolution can now be used to tune protein turnover rates (33–35). However, before setting out to reduce enzyme turnover it is essential to define target enzymes and to understand why they turn over fast in the first place. Accordingly, here we calculate and compare the life spans of enzymes from three kingdoms using the criterion of “catalytic cycles until replacement” (CCR) (33), defined as the moles of substrate converted per mole of enzyme before the enzyme is replaced, i.e., the following:CCR=Metabolic flux rateEnzyme replacement rate.[1]CCR is the in vivo equivalent of the ex vivo “total turnover number” mentioned above but is a preferable term as it avoids confusion with the term “turnover number,” a synonym in enzymology for k_cat (20). CCR is envisioned as a potential constant, with reaction wear-and-tear being matched with degradation rates to maintain CCR as a factor hardwired to the structural and (bio)chemical stability of a given enzyme (33). We then compare each enzyme’s CCR to its reaction chemistry and across kingdoms to find shared attributes underlying CCR values. Our findings imply that CCRs are commonly influenced by random collateral damage from the reaction catalyzed and that enzymes could be engineered to reduce this damage and its attendant enzyme replacement costs. More generally, the findings point to catalysis-related accidents as a sizeable but underrecognized cause of enzyme failure and replacement.     

Lipoteichoic acid polymer length is determined by competition between free starter units

Carbohydrate polymers exhibit incredible chemical and structural diversity, yet are produced by polymerases without a template to guide length and composition. As the length of carbohydrate polymers is critical for their biological functions, understanding the mechanisms that determine polymer length is an important area of investigation. Most Gram-positive bacteria produce anionic glycopolymers called lipoteichoic acids (LTA) that are synthesized by lipoteichoic acid synthase (LtaS) on a diglucosyl-diacylglycerol (Glc₂DAG) starter unit embedded in the extracellular leaflet of the cell membrane. LtaS can use phosphatidylglycerol (PG) as an alternative starter unit, but PG-anchored LTA polymers are significantly longer, and cells that make these abnormally long polymers exhibit major defects in cell growth and division. To determine how LTA polymer length is controlled, we reconstituted Staphylococcus aureus LtaS in vitro. We show that polymer length is an intrinsic property of LtaS that is directly regulated by the identity and concentration of lipid starter units. Polymerization is processive, and the overall reaction rate is substantially faster for the preferred Glc₂DAG starter unit, yet the use of Glc₂DAG leads to shorter polymers. We propose a simple mechanism to explain this surprising result: free starter units terminate polymerization by displacing the lipid anchor of the growing polymer from its binding site on the enzyme. Because LtaS is conserved across most Gram-positive bacteria and is important for survival, this reconstituted system should be useful for characterizing inhibitors of this key cell envelope enzyme.

All cell surfaces are rich in carbohydrate polymers that act as structural components, scaffolds for other molecules, and participants in signaling processes (1). The biological functions of a carbohydrate polymer are often greatly affected by its length. For example, depending on molecular weight, hyaluronic acid polymers can promote cell migration, differentiation, and inflammation or can inhibit these processes (2, 3). Similarly, the number of repeat units in bacterial O-antigen has a profound effect on complement activation and host cell uptake (4, 5). Unlike protein and nucleic acid polymers, which are assembled on a template that determines both length and composition, carbohydrate polymers are assembled without the use of a template. Template-independent length regulation is not as precise as template-directed polymerization, but physiological lengths of carbohydrate polymers typically fall into a defined range that is important for function (6). How different polymerases achieve length control is a fundamental question in the field.Several mechanisms for carbohydrate polymer length determination have been described. Some polymerases include a “molecular ruler” domain that measures the polymer against a portion of the enzyme (7), some use a dedicated “termination enzyme” to control length (8), and others rely on repeat unit concentration to control polymerization (9). These mechanisms are not mutually exclusive and can act together to control length (10, 11). The degree to which a polymerase is processive also influences product length. Processivity, a fundamental property of polymerases, refers to the number of elongation steps that occur without release of the growing polymer (12). A polymerase may be partially processive, in that more than one monomer addition occurs while the polymer is bound to the enzyme, but the polymer can be released and then rebind to continue elongation. A polymerase may also act in a distributive manner, where the growing polymer is released after each round of monomer addition. While some general mechanisms and aspects of length control for carbohydrate polymerases are known, here we describe a previously unknown mechanism for length regulation of a common type of lipoteichoic acid (LTA), a cell surface polymer that is crucially important to the physiology of most Gram-positive bacteria (13, 14).In the Gram-positive pathogen Staphylococcus aureus (Sa), LTA is a membrane-anchored poly(glycerol-phosphate) polymer involved in virulence (15–19), regulation of cell size and division (20–23), and osmotic stability (24, 25) (Fig. 1A). Sa LTA is assembled by the conserved lipoteichoic acid synthase (LtaS) on the cell surface using glucose(β1,6)-glucose(β1,3)-diacylglycerol (Glc₂DAG) as the membrane-anchored “starter unit” (20, 26). The polymer elongates in a process that involves the repeated transfer of phosphoglycerol units from phosphatidylglycerol (PG) to a catalytic threonine in LtaS (T300) and then to the tip of the growing polymer (Fig. 1B) (27–29). Repeat units may be modified by D-alanyl esters or, less commonly, GlcNAc moieties (24, 30). Because LTA is so important for Sa survival (13, 14, 21, 22), LtaS is a proposed target for antibiotics, and understanding its behavior may facilitate inhibitor development.Open in a separate windowFig. 1.LTA is a lipid-anchored polymer assembled from Glc₂DAG and PG on the bacterial cell surface. (A) Chemical structure of LTA from Sa. Phosphoglycerol repeat units may be modified with D-alanine esters or GlcNAc moieties. (B) Mechanism of LTA synthesis by LtaS. Phosphoglycerol units are transferred from PG to residue T300 to form a covalent intermediate, releasing DAG. Phosphoglycerol is then transferred to a Glc₂DAG starter unit to form GroP-Glc₂DAG. Additional repeat units are added to the glycerol tip of the polymer. (C) In Sa, PgcA and GtaB synthesize UDP-glucose from glucose-6-phosphate. UgtP uses UDP-glucose and DAG to make Glc₂DAG. LtaA exports Glc₂DAG to the cell surface. LtaS transfers phosphoglycerol units derived from PG to T300, releasing DAG for recycling. (D) Anti-LTA Western blot of Sa RN4220 wild-type (wt) or ΔugtP lysates. ΔugtP mutants lack Glc₂DAG, and LTA is instead polymerized directly on PG (20).Glc₂DAG, the starter unit for LTA polymerization, is biosynthesized on the cytoplasmic leaflet of the membrane by the sequential action of three enzymes: the phosphoglucose mutase PgcA, the UTP-glucose-1-phosphate uridylyltransferase GtaB, and the diacylglycerol β-glucosyltransferase UgtP (also called YpfP) (15, 20). Glc₂DAG is exported to the cell surface by the flippase LtaA (Fig. 1C) (15). An interesting feature of LtaS is that it can use PG as an alternative starter unit if Glc₂DAG synthesis or export is blocked (20). However, polymers formed on this alternative starter unit (PG-LTA) are significantly longer than polymers formed on Glc₂DAG (Glc₂DAG-LTA, Fig. 1D) (15, 23), and cells that make these longer polymers have cell division defects (20, 23), are much less virulent (15, 16), and are more sensitive to beta-lactam antibiotics and other cell envelope stresses (23). Whether the shorter polymers assembled on Glc₂DAG reflect the intrinsic behavior of LtaS or the action of other cellular factors is an important question that cannot be definitively answered with genetic approaches.Here we used in vitro reconstitution to test whether the identity of the LTA membrane anchor determines the length of the polymers that LtaS synthesizes. We show that the length differences observed between wild-type and mutant cells lacking Glc₂DAG are recapitulated in a proteoliposome system that contains only purified LtaS, PG, and either Glc₂DAG or an alternative anchor. Based on our studies, we propose a model for how polymer length can be controlled in polymerases that operate without a template.     

“Soft” oxidative coupling of methane to ethylene: Mechanistic insights from combined experiment and theory

The oxidative coupling of methane to ethylene using gaseous disulfur (2CH₄ + S₂ → C₂H₄ + 2H₂S) as an oxidant (SOCM) proceeds with promising selectivity. Here, we report detailed experimental and theoretical studies that examine the mechanism for the conversion of CH₄ to C₂H₄ over an Fe₃O₄-derived FeS₂ catalyst achieving a promising ethylene selectivity of 33%. We compare and contrast these results with those for the highly exothermic oxidative coupling of methane (OCM) using O₂ (2CH₄ + O₂ → C₂H₄ + 2H₂O). SOCM kinetic/mechanistic analysis, along with density functional theory results, indicate that ethylene is produced as a primary product of methane activation, proceeding predominantly via CH₂ coupling over dimeric S–S moieties that bridge Fe surface sites, and to a lesser degree, on heavily sulfided mononuclear sites. In contrast to and unlike OCM, the overoxidized CS₂ by-product forms predominantly via CH₄ oxidation, rather than from C₂ products, through a series of C–H activation and S-addition steps at adsorbed sulfur sites on the FeS₂ surface. The experimental rates for methane conversion are first order in both CH₄ and S₂, consistent with the involvement of two S sites in the rate-determining methane C–H activation step, with a CD₄/CH₄ kinetic isotope effect of 1.78. The experimental apparent activation energy for methane conversion is 66 ± 8 kJ/mol, significantly lower than for CH₄ oxidative coupling with O₂. The computed methane activation barrier, rate orders, and kinetic isotope values are consistent with experiment. All evidence indicates that SOCM proceeds via a very different pathway than that of OCM.

The oxidative coupling of methane (OCM) with O₂ would seem to be a concise, direct route to convert methane, one of the most Earth-abundant carbon sources (1), to ethylene (2CH₄ + O₂ → C₂H₄ + 2H₂O), a key chemical intermediate (2, 3), and this process has been extensively studied (1, 4–19) since 1982 (20). Nevertheless, the widespread use of OCM is challenged by methane overoxidation to CO₂ and other oxygenates. Furthermore, the severe reaction conditions of nonoxidative pathways (2, 21–28) typically risk carbon deposition and catalyst deactivation (2, 21–26). In preliminary studies, we reported a 2CH₄ + S₂ → C₂H₄ + 2H₂S coupling process that moderates the methane overoxidation driving force using gaseous disulfur (S₂) as a “soft” oxidant (SOCM; Fig. 1A) (29). S₂ is isoelectronic with O₂, the major sulfur vapor species at 700 to 925 °C (30–32), and is a less aggressive oxidant than O₂ (33). In this scenario, elemental sulfur is recovered from the H₂S coproduct via the known Claus process (Fig. 1B) (30), in a cycle where sulfur mediates/moderates the high nonselective O₂ reactivity. SOCM achieved promising ethylene selectivity, raising intriguing mechanistic questions and the possibility of higher selectivity. Methane + S_2(g) ethylene selectivities near ∼20% are achieved over a PdS/ZrO₂ catalyst (29), and oxide precatalysts give selectivities near 33% (34).Open in a separate windowFig. 1.Energetic comparison between the oxidative coupling of methane with O₂ (OCM) and with S₂ (SOCM) and the pathway to recover elemental sulfur from H₂S. (A) Gibbs free energy of desired and overoxidation processes in OCM and SOCM at 800 and 1,050 °C. (B) Industrialized catalytic Claus process used to recover elemental sulfur from H₂S.Nevertheless, in contrast to extensive OCM (17, 35–39) and nonoxidative CH₄ coupling studies (40), far less is known about the SOCM reaction pathway. Post-SOCM X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and elemental analysis (29, 34) indicate that the oxide precatalysts are predominantly sulfided. Density functional theory (DFT) analyses of molybdenum sulfide catalysts suggest that methane is activated at M–S or S–S sites to form surface-bound CH₃* species which dehydrogenate to form CH₂* (methylidene) species, which then couple to produce C₂H₄. It was proposed that CH₃* species can also desorb as methyl radicals which couple to form ethane (29). The overoxidation product, CS₂, was suggested to form via sulfur addition to methylidene surface intermediates (29).Kinetic, mechanistic, and theoretical analyses are needed to better understand the CH₄ conversion pathways to C₂H₄ and other products. In principle, there are two plausible pathways following methane activation: 1) H abstraction from adsorbed methyl species forms methylidene (CH₂*) and methylidyne (CH*) species then couple to C₂ products or undergo oxidation to CS₂ or 2) coupling of surface or gas phase methyl species form ethane, which then dehydrogenates to form ethylene or oxidizes to CS₂. For further SOCM optimization it is important to determine which pathways are operative, their relative rates, and the C₂ and CS₂ formation sites.Here we investigate SOCM pathways over a sulfided Fe₃O₄ precatalyst which affords C₂H₄ selectivities near 33%, complete oxide to sulfide conversion, minimal carbon deposition (coking), and 48-h SOCM stability at 950 °C (34). We first summarize SOCM phenomenology, followed by analysis of the Fe phases during sulfurization and SOCM. Next, kinetic/mechanistic studies focus on the methane and S₂ reaction orders, activation energetics, and isotope effects and probe the pathways governing C₂ vs. CS₂ formation. Complementary DFT calculations focus on reaction mechanisms, the active sites, and their role in product formation. The results are used in a microkinetic model to simulate reaction rates, apparent activation barriers, and reaction rate orders and to compare with experiment. Finally, SOCM and OCM are compared, revealing that they follow distinctly different pathways.     

Capillary equilibrium of bubbles in porous media

In geologic, biologic, and engineering porous media, bubbles (or droplets, ganglia) emerge in the aftermath of flow, phase change, or chemical reactions, where capillary equilibrium of bubbles significantly impacts the hydraulic, transport, and reactive processes. There has previously been great progress in general understanding of capillarity in porous media, but specific investigation into bubbles is lacking. Here, we propose a conceptual model of a bubble’s capillary equilibrium associated with free energy inside a porous medium. We quantify the multistability and hysteretic behaviors of a bubble induced by multiple state variables and study the impacts of pore geometry and wettability. Surprisingly, our model provides a compact explanation of counterintuitive observations that bubble populations within porous media can be thermodynamically stable despite their large specific area by analyzing the relationship between free energy and bubble volume. This work provides a perspective for understanding dispersed fluids in porous media that is relevant to CO₂ sequestration, petroleum recovery, and fuel cells, among other applications.

Bubbles are generated, trapped, and mobilized within porous media as a consequence of incomplete fluid–fluid displacements (1, 2), phase changes (3, 4), chemical and biochemical reactions (5, 6), or injection of emulsified fluids and foams (7, 8). Compared to continuously connected phases, the behavior of dispersed bubbles, or ganglia, are far less understood. In particular, the thermodynamic stability of bubbles, despite their large specific surface area, remains a puzzle. The difficulty comes from the fact that each bubble can attain a volume (V), topology, and capillary pressure (P_c) that is distinct from other bubbles in the medium (9). The variability poses challenges to understanding the transport and trapping mechanisms of bubbles in geologic CO₂ sequestration (10, 11), hydrocarbon recovery (12, 13), fuel cell water management (14, 15), and vadose zone oxygen supply (16, 17).The dominant factor controlling a bubble’s behavior in a porous medium is capillarity, which is typically much larger than either viscous, gravitational, or inertial forces (18, 19). Capillary pressure, P_c, allows a closure relationship for two-phase Darcy Eqs. (20–22) and influences thermodynamic properties like phase partition (23). Capillary pressure is derived from the Young–Laplace equation P_c = γκ, where γ is the interfacial tension and κ is the surface curvature. In an open space without obstacles, a bubble spontaneously evolves into a sphere to minimize its total interfacial energy. Thus, P_c is a continuous and monotonically decreasing function of V (Fig. 1A). However, in a porous medium, bubble’s P_c–V relation is more complicated due to the geometric confinement imposed by the porous structure and topological evolution (24). A bubble can no longer remain spherical as it grows in size but must conform to the geometry of the pore(s) it occupies. Therefore, a bubble’s P_c is a function of not only its volume and interfacial tension but also its topology as dictated by the confining porous medium, as confirmed by recent laboratory experiments and numerical simulations (25–29). The mere presence of confinement therefore engenders a host of phenomena that would otherwise be absent, such as capillary trapping (30, 31), anticoarsening of bubble populations (32, 33), and complex ganglion dynamics (11, 18). Furthermore, theoretical studies in mathematical topology (28, 34, 35) prove that immiscible fluids can be fully characterized by d+1 Minkowski functionals, where d is the problem dimension. Such characterizations remove the path-dependent (or hysteretic) behavior common to these systems (34, 35).Open in a separate windowFig. 1.(A) Spherical bubbles inside a bulk fluid. (B) Micromodel observations show that bubbles are nonspherical in porous media and may occupy multiple pores. This image is from SI Appendix, Movie S1. (C) A 2D porous medium comprised of an ordered array of identical circular grains. A bubble occupying multiple pores including a zoom-in to a portion of it. (D) Illustration of the full state. (E) Illustration of the critical state. (F) Decomposition of a bubble into four distinct parts: minor arc menisci shown by dark blue cap-shaped regions, throats shown by light blue diamond-shaped regions, inner bulk bodies shown by red star-shaped regions, and major arc menisci shown by dark green cap-shaped regions.Recent developments in microfluidics and micro computed tomography imaging allow detailed pore-scale visualizations of fluids inside porous media, including the morphology of bubbles and ganglia (25, 36–39). Garing et al. (25) experimentally measured the equilibrium capillary pressure of trapped air bubbles inside sandstone and bead-pack samples. They found that, unlike bubbles within a bulk fluid, the P_c of trapped bubbles shows no clear dependence on V and seems to fall within a bounded interval, except for vanishingly small V. Xu et al. (40) proposed an empirical correlation for the P_c trapped bubbles based on microfluidic observations. In this correlation, as V increases, P_c decreases until a minimum is reached and then increases linearly. In the first stage, the bubble is unconfined, whereas in the second, it is reshaped by the surrounding solid walls. The proposed correlation, however, is only valid for bubbles in a single pore and not bubbles that span multiple pores. The latter seems to be rather common in nature as evidenced by recent direct observations (Fig. 1B) (2, 25).Here, we propose a simple conceptual model to describe the equilibrium states of a bubble with arbitrary size trapped inside a porous medium. The model accounts for the bubble’s morphology, the geometry of the solid matrix, and the wettability between the two. We derive all metastable configurations of the bubble analytically and highlight the thermodynamic states the bubble assumes when it is static, growing, or shrinking. We also show that the relationship between surface free energy (F) and volume (V) of large bubbles is approximately linear, which explains the previously counterintuitive observation that such bubbles are thermodynamically stable despite having large surface areas. Our work provides a step toward understanding the capillary state, stability, and evolution of dispersed immiscible fluids in porous media.     

Superelastic oxide micropillars enabled by surface tension–modulated 90° domain switching with excellent fatigue resistance

Superelastic materials capable of recovering large nonlinear strains are ideal for a variety of applications in morphing structures, reconfigurable systems, and robots. However, making oxide materials superelastic has been a long-standing challenge due to their intrinsic brittleness. Here, we fabricate ferroelectric BaTiO₃ (BTO) micropillars that not only are superelastic but also possess excellent fatigue resistance, lasting over 1 million cycles without accumulating residual strains or noticeable variation in stress–strain curves. Phase field simulations reveal that the large recoverable strains of BTO micropillars arise from surface tension–modulated 90° domain switching and thus are size dependent, while the small energy barrier and ultralow energy dissipation are responsible for their unprecedented cyclic stability among superelastic materials. This work demonstrates a general strategy to realize superelastic and fatigue-resistant domain switching in ferroelectric oxides for many potential applications.

Superelastic materials are capable of recovering large amount of nonlinear “plastic” strains, way beyond their linear elastic regimes (1–4). They are ideal for a variety of applications from morphing structures, reconfigurable systems, to robots (5–8). The effects have traditionally been associated with macroscopically compliant/ductile rubbers (2) or microscopically phase-transforming shape memory alloys (SMAs) (7–11). The only macroscopically brittle oxide recently discovered to be superelastic is ZrO₂-based micropillars or particles (12–20), which is realized via austenite-martensite phase transformation similar to SMAs. Although ultimate strengths approaching the theoretical limit have been demonstrated in nanoscale samples (21, 22), long fatigue life is elusive, which is arguably more important for most applications. As a matter of fact, poor fatigue life has been a long-standing challenge for oxide ceramics in general (23, 24). Even for ductile SMAs that enjoy excellent fatigue life, irrecoverable residual strains gradually accumulate over cycling, leading to substantial variations in stress–strain curves at different cycles (9, 10, 25). We overcome these difficulties by reporting superelastic barium titanate (BaTiO₃ [BTO]) micropillars enabled by surface tension–modulated 90° domain switching, which exhibit excellent fatigue resistance, while bulk BTO crystals or ceramics are rather brittle. The demonstration of over one million cycles of loading and unloading without accumulating residual strains or noticeable variation in stress–strain curves is unprecedented among superelastic materials.BTO is a ferroelectric oxide exhibiting modest piezoelectric strains around 0.1 to 0.2% (26) and fracture toughness of ∼1 MPa ⋅ m^1/2, and thus it is quite brittle (27). Considerable research efforts have been devoted to enhancing its electric field–induced strain via 90° ferroelectric domain switching (28–30). However, the process is often irreversible, and external mechanisms such as restoring force (28, 29) and internal mechanisms such as defect pinning (30) have to be invoked to make the electrostrain recoverable. Nevertheless, it hints at the possibility of BTO being made superelastic by taking advantage of the stress-induced 90° domain switching (6). Earlier works suggest that surface tension induces an in-plane compressive stress that favors the axial polarization in one-dimensional ferroelectrics at small size (31, 32), which may provide the necessary restoring mechanism for the stress-switched domains. Thus, if a compressive axial force is applied, reversible domain switching may occur during unloading, leading to superelasticity. To verify this hypothesis, we fabricated single-crystalline BTO micropillars from [001]-oriented bulk crystals (SI Appendix, Fig. S1A) via focused ion beam (FIB), as detailed in Materials and Methods and SI Appendix, Fig. S1B. The diameters (Φ) of the micropillars range from 0.5 μm to 5 μm, with their height to diameter ratio fixed at 3. No visible defects can be seen from the scanning electron microscopy (SEM) images of these micropillars shown in Fig. 1 A–D, and their surfaces appear to be quite smooth, suggesting that no apparent damages are induced by FIB.Open in a separate windowFig. 1.Superelastic BTO micropillars below a critical size. (A–D) SEM images of the micropillars with Φ = 5, 3, 2, and 0.5 μm. (E–G) The first and second cycles of stress–strain curves for BTO micropillars with Φ = 5, 2, and 0.5 μm. (H) S_r/S_max and ΔW/W_max during the first cycle for BTO micropillars of different diameters. Here, S_r and S_max denote the residual strain and the maximum strain (SI Appendix, Fig. S6A), while ΔW and W_max are energy dissipated and stored in the first cycle, respectively (SI Appendix, Fig. S6F).     

Appraisal of sedimentary alkenones for the quantitative reconstruction of phytoplankton biomass

Marine primary productivity (PP) is the driving factor in the global marine carbon cycle. Its reconstruction in past climates relies on biogeochemical proxies that are not considered to provide an unequivocal signal. These are often based on the water column flux of biogenic components to sediments (organic carbon, biogenic opal, biomarkers), although other factors than productivity are posited to control the sedimentary contents of the components, and their flux is related to the fraction of export production buried in sediments. Moreover, most flux proxies have not been globally appraised. Here, we assess a proxy to quantify past phytoplankton biomass by correlating the concentration of C₃₇ alkenones in a global suite of core-top sediments with sea surface chlorophyll-a (SSchla) estimates over the last 20 y. SSchla is the central metric to calculate phytoplankton biomass and is directly related to PP. We show that the global spatial distribution of sedimentary alkenones is primarily correlated to SSchla rather than diagenetic factors such as the oxygen concentration in bottom waters, which challenges previous assumptions on the role of preservation on driving concentrations of sedimentary organic compounds. Moreover, our results suggest that the rate of global carbon export to sediments is not regionally constrained, and that alkenones producers play a dominant role in the global export of carbon buried in the seafloor. This study shows the potential of using sedimentary alkenones to estimate past phytoplankton biomass, which in turn can be used to infer past PP in the global ocean.

Global carbon distribution between the ocean and the atmosphere regulates global climate on Earth. This distribution is primarily controlled by marine primary productivity (PP) and phytoplanktonic organisms, which transforms atmospheric CO₂ into organic matter. Only a fraction of this produced organic matter is exported to the deep ocean. Global models estimate that 48 PgC·y⁻¹ are produced in ocean surface waters (1), while 6 PgC·y⁻¹ (2) are exported out from the photic zone and 0.15 PgC·y⁻¹ are buried in sediments (3). Exported organic carbon is out of contact with the atmosphere on decadal-to-millennial timescales or longer once is buried in the seafloor, which exerts a major control on global climate by regulating the partial pressure of atmospheric CO₂ (4). Hence, estimating marine PP, export, and burial productivity changes during past key climatic periods (e.g., glacial–interglacial transitions) is essential to understand our present climate and predict its evolution in the future.To infer past PP, a range of proxies based on the fluxes of biogenic components are available (5–7). As flux proxies, they are related to changes in past export productivity, which are assumed to be proportional to surface PP in paleoreconstructions. However, depositional factors such as oxygen or ballasting effect are thought to be important in controlling organic matter export from the upper water column to sediments (8–10), and thus, sedimentary organic proxies concentration. The relative weights of the factors that control the spatial variability of organic matter concentration in sediments are still unconstrained, which leads to some uncertainty on the applicability of organic matter proxies to infer PP (7). Consequently, available proxies are sometimes interpreted to infer either changes in PP or depositional conditions (11).One of the common approaches to reconstruct PP relies on the measurement of C₃₇ di- and tri- unsaturated methyl ketones (i.e., C₃₇ alkenones) concentrations or fluxes in sediments (12–18). These organic molecules are biomarkers of the ubiquitous coccolithophore Emiliania huxleyi, which is the principal source of alkenones and the most abundant coccolithophore in the modern pelagic ocean (19–24). Geophyrocapsa oceanica and other coccolithophoral species from the same genera are also considered important alkenones producers nowadays (20).In this study, we evaluate the potential use of sedimentary C₃₇ alkenones content to infer past phytoplankton biomass at a global scale through the comparison of their spatial variability in a global compilation of core-top sediments with sea surface chlorophyll-a (SSchla) (Fig. 1). This is the primary pigment of photosynthesis and is present in all photosynthetic phytoplankton species. Its concentration in surface waters is commonly used as an indicator of phytoplankton biomass and to infer PP (25, 26). On a global scale, its concentration in surface waters is estimated by remote sensing (27). We also assess the effect of oxygen on the spatial accumulation of alkenones in sediments by comparing its concentration in bottom waters with alkenones abundance on a global scale.Open in a separate windowFig. 1.Global core-top sediments distribution. Lines delineate distinct biogeochemical regions defined on the basis of phytoplankton community, temperature, and nutrient concentration (44). SA, subarctic; SO, Southern Ocean; ST, subtropics; T, tropics.