4D visualization of embryonic, structural crystallization by single-pulse microscopy

In many physical and biological systems the transition from an amorphous to ordered native structure involves complex energy landscapes, and understanding such transformations requires not only their thermodynamics but also the structural dynamics during the process. Here, we extend our 4D visualization method with electron imaging to include the study of irreversible processes with a single pulse in the same ultrafast electron microscope (UEM) as used before in the single-electron mode for the study of reversible processes. With this augmentation, we report on the transformation of amorphous to crystalline structure with silicon as an example. A single heating pulse was used to initiate crystallization from the amorphous phase while a single packet of electrons imaged selectively in space the transformation as the structure continuously changes with time. From the evolution of crystallinity in real time and the changes in morphology, for nanosecond and femtosecond pulse heating, we describe two types of processes, one that occurs at early time and involves a nondiffusive motion and another that takes place on a longer time scale. Similar mechanisms of two distinct time scales may perhaps be important in biomolecular folding.     

Retrovirus envelope protein complex structure in situ studied by cryo-electron tomography

We used cryo-electron tomography in conjunction with single-particle averaging techniques to study the structures of frozen-hydrated envelope glycoprotein (Env) complexes on intact Moloney murine leukemia retrovirus particles. Cryo-electron tomography allows 3D imaging of viruses in toto at a resolution sufficient to locate individual macromolecules, and local averaging of abundant complexes substantially improves the resolution. The averaging of repetitive features in electron tomograms is hampered by a low signal-to-noise ratio and anisotropic resolution, which results from the "missing-wedge" effect. We developed an iterative 3D averaging algorithm that compensates for this effect and used it to determine the trimeric structure of Env to a resolution of 2.7 nm, at which individual domains can be resolved. Strikingly, the 3D reconstruction is shaped like a tripod in which the trimer penetrates the membrane at three distinct locations approximately 4.5 nm apart from one another. The Env reconstruction allows tentative docking of the x-ray crystal structure of the receptor-binding domain. This study thus provides 3D structural information regarding the prefusion conformation of an intact unstained retrovirus surface protein.     

Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes

Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure–activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein–nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is generally accepted to have originated from an animal reservoir, most likely bats, which after adaptive changes jumped the species barrier to infect humans in late 2019. Although the resulting coronavirus disease 2019 (COVID-19) is generally a mild respiratory disease in the young, it can be severe in elderly persons and those with comorbidities. The virus has spread around the globe; as of March 2022, it has resulted in nearly 18 million deaths (1), many more hospitalizations, and profound economic and social disruption. Vaccines have shown to be effective (2, 3). Repurposing of existing drugs, including the antiviral compound remdesivir and dexamethasone, has delivered benefits (4), with other drugs (molnupiravir, fluvoxamine, and Paxlovid) also showing significant promise, as reviewed by Wen et al. (5). Moreover, injection of monoclonal antibodies has shown promise in preventing serious disease (6). However, there remains strong interest in new therapies that reduce transmission and decrease disease severity, particularly ones that could be deployed rapidly. In addition, the virus has evolved to escape therapeutic monoclonal antibodies (7–9), so these therapeutics may need to be modified to remain active against emerging variants.Isolating antibodies by naïve library screening is very rapid, requiring only the target antigen. Phage display methods (10) have been applied to diverse arrays of antibodies which by repeated cycling identify the strongest binders in an iterative process (11). However, binding strengths of the naïve library hits are usually not strong enough for the agents to be useful, which is perhaps unsurprising, as libraries can only sample a small portion of the available diversity. One solution to this problem is to improve the binding affinity through a process known as affinity maturation (12), where the potential recognition sites (usually the complementarity-determining regions [CDRs] of antibodies) of the initial binders are mutated and the strongest binding mutants are selected (13). Such laboratory-based approaches mimic the natural selection process that operates in mammals to produce high-affinity antibodies to foreign antigens (14).The epitope binding site of single-domain antibodies derived from the heavy chain–only antibodies of camelids is contained within a single compact variable domain of about 130 amino acids (nanobody) (15, 16). Epitope recognition commonly uses CDR1 (typically residues 28 to 34), CDR2 (typically residues 48 to 54), and the longer CDR3 (typically residues 97 to 114). Nanobodies and their derivatives have a long history in structural biology, where they have contributed to many structural studies by stabilizing conformational states for both electron microscopy (EM) and crystallography (for a recent review, see ref. 17) or adding sufficient size to enable EM studies (18). There are already multiple studies of nanobodies that neutralize SARS-CoV-2 (19–23) as well as their use as tools for the structural study of viral proteins (24). Since nanobodies are inherently compact, they are particularly suitable for maturation approaches. As an alternative to maturation, very large (10¹² sequences) synthetic libraries of binders, known as sybodies, have been screened to identify tight binders (25). Single-chain human antibodies have also been engineered and used against SARS-CoV-2 (26, 27). However, the application of computational approaches to maturation has been limited.A recent review analyzed structures of human antibodies bound to their targets from HIV (28). Improved binding arose from the optimization of the complementarity between antibody and antigen, including through an increase in the surface area buried upon binding and in the rigidity of the loops preorganized for binding (28). Deep sequencing then allowed the pathway by which these mutations were selected to be reconstructed. However, there are very few systematic studies of nanobody selection and maturation with a single antigen, which is necessary if deep learning approaches are to be brought to bear. In this context, structural insight could be particularly helpful since it can identify those changes which directly and indirectly affect binding to the antigen.To develop an understanding of the structural basis of nanobody binding affinity, we carried out the biophysical and structural characterization of a series of six nanobodies targeting the receptor binding domain (RBD) of SARS-CoV-2 spike protein, comprising a hit from screening a naïve nanobody library and five affinity-matured mutants derived from this parental binder; two of the mutants have been shown to be potently neutralize the virus (29). Using these data, we identified the key conformational properties that drive the affinity of this class of molecule. Based on cryo-EM data and a computational approach, we then engineered a hybrid nanobody with a CDR3 sequence that improved the binding affinity to the spike protein. We suggest that the quantitative estimate of the conformational entropy of the spike-nanobody complexes from experimental EM maps is helpful in the rational maturation of nanobodies against their target.     

Kin selection explains the evolution of cooperation in the gut microbiota

Through the secretion of “public goods” molecules, microbes cooperatively exploit their habitat. This is known as a major driver of the functioning of microbial communities, including in human disease. Understanding why microbial species cooperate is therefore crucial to achieve successful microbial community management, such as microbiome manipulation. A leading explanation is that of Hamilton’s inclusive-fitness framework. A cooperator can indirectly transmit its genes by helping the reproduction of an individual carrying similar genes. Therefore, all else being equal, as relatedness among individuals increases, so should cooperation. However, the predictive power of relatedness, particularly in microbes, is surrounded by controversy. Using phylogenetic comparative analyses across the full diversity of the human gut microbiota and six forms of cooperation, we find that relatedness is predictive of the cooperative gene content evolution in gut-microbe genomes. Hence, relatedness is predictive of cooperation over broad microbial taxonomic levels that encompass variation in other life-history and ecology details. This supports the generality of Hamilton’s central insights and the relevance of relatedness as a key parameter of interest to advance microbial predictive and engineering science.

Managing complex microbial communities (MCs) is key to a range of applications in the midst of our society’s challenges from microbiome manipulation (1) to sustainable food production (2) and climate regulation (3). The successful engineering of such communities requires the field of MCs and microbiome research to advance into more predictive science (4, 5). Crucial to this are theories of broad predictive ability. Firstly, such theories allow predictions that consistently hold across the vast diversity of microbial species making up those communities, and, secondly, they facilitate the translation of theory into actionable tools.Cooperative interactions are central to microbes’ lives, as well as how they interact with and modify their environment (6–13). Through the secretion of “public goods,” such as toxins, enzymes, or signaling molecules, microbes cooperatively exploit and modify their habitat (14, 15). Recent “omics” studies have demonstrated the important role of such cooperative interactions in the evolution and function of real communities (16, 17), including diseases-associated communities (18). To predict and engineer the dynamics and evolution of MCs, it is therefore essential to understand the factors having a broad influence on the evolution of cooperation in the species making up these communities.How cooperation evolves is puzzling because populations exhibiting such behavior are at risk from invasion by selfish cheats, reaping the reward without paying any of the cost (19). Hamilton’s kin-selection theory provides an explanation: Even if sacrificing its own reproduction by helping a close relative reproduce, a cooperative individual can still pass on its genes to the next generation, albeit indirectly (20). Therefore, altruism is favored when fitness costs to the helper are overcome by benefits provided to the recipient weighted by their genetic relatedness (rb > c, “Hamilton’s rule”). This gives a central role to genetic relatedness, because it limits those indirect fitness benefits (21) (Fig. 1A). Hamilton’s theory generates a prediction of great generality: All else being equal, increased relatedness should lead to more cooperation. Contrary to predictions based on specific mechanisms [e.g., pleiotropy (22) or greenbeard genes (23, 24)] or that apply to a limited amount of taxa [e.g., particular scenarios calling upon preadaptations (25, 26)], the generality of Hamilton’s prediction is useful in that it identifies a unifying parameter (27). In the context of mastering MCs that are hugely diverse, such unifying principle is key. The question is then whether this is true in practice: Is relatedness broadly predictive of the evolution of cooperation in microbes?Open in a separate windowFig. 1.Genetic relatedness in the human gut microbiome. (A) Schematic illustration of indirect fitness benefits. The cooperative cell loses the opportunity to produce c daughter cells (cost c). The help provided to the recipient cells allows them to each produce an additional b daughter cells (benefit b). The cooperative genes of the altruist cell are “indirectly transmitted” if the benefits provided enhance, on average, the reproduction of cells that also carry those cooperative genes, i.e., are genetically related; r > 0. (B) Methods schematic summary. Detailed within- and across-samples core genome size and nucleotide diversity are given in Dataset S1. SNPs, single-nucleotide polymorphisms. (C) Relatedness measures obtained for 101 species of the human gut microbiome. Vertical ticks are single point estimates of relatedness. The number of point estimates (i.e., number of hosts within which each species was found) is indicated on the right. The black dots represent the mean. Blue ticks are values between 25% and 75% quantiles.Although kin selection has been a leading explanation for the evolution of cooperation from microorganisms to vertebrates in the field and in the laboratory (12, 13, 19, 23, 24, 28–33), three main arguments cast doubt on its generality and predictive power in microbes. Firstly, even if relatedness drives cooperation, the direction of its effect may depend on the details of the biology of a particular cooperative behavior. For example, it has been shown that when a public good can be partly privatized (e.g., with strain-specific receptors), the public good becomes a competitive trait, therefore leading to a negative relationship between relatedness and the level of public-good production (34). Such variability in the direction of effect means that prediction may not be consistent across different types of cooperative behavior and species. Secondly, it has been suggested that interspecies interactions (i.e., when public goods provide interspecific benefit) may render relatedness unimportant at driving cooperation within species. This has been observed in the production of siderophores (a secreted iron-scavenging molecule acting as a public good) in Pseudomonas aeruginosa. In conditions such that siderophores also provided cross-species benefits (environment detoxification), the addition of a compost community allowed the growth of noncooperators, irrespective of the level of relatedness (35). This challenges the effective importance of relatedness in real-world, complex communities. Third, theoretical work predicts that the population-genetics effects at work in the kin-selection framework may be unimportant in microbes owing to strong selection (25, 36, 37). Together, these arguments suggest that intraspecific relatedness may have minor or idiosyncratic effects on the evolution of cooperation in microbes.Although these studies highlight potential limitations in the power of relatedness to predict the evolution of microbial cooperation, they do not assess their actual importance across the microbial tree of life. The ultimate test of the broad role of relatedness in the evolution of cooperation is to use a comparative analysis to assess whether relatedness can predict the phylogenetic distribution of cooperative traits. While such studies exist for a range of animal species [shrimps (38), mammals (39, 40), birds (41), and Hymenoptera (42, 43)], none have been performed in microbes. Conducting a comparative analysis in microbes is more than a mere additional test of Hamilton’s rule. Microbes constitute an excellent system to test the claim of generality: It assesses relatedness predictive power over a broad set of ecological idiosyncrasies by 1) including a large number of phylogenetically distant species with different ecology, 2) comparing a variety of cooperative behaviors that have very different ecological contexts (while most existing studies focus on a single cooperative behavior), and 3) using actual genomic relatedness from sequencing data, rather than of proxy such as promiscuity level (41).We conducted such phylogenetic comparative analysis across the full diversity of the human gut microbiota, encompassing 37 genera, testing the effect of relatedness on six different forms of microbial cooperation.     

From the Cover: Discovery of the surface polarity gradient on iridescent Morpho butterfly scales reveals a mechanism of their selective vapor response

For almost a century, the iridescence of tropical Morpho butterfly scales has been known to originate from 3D vertical ridge structures of stacked periodic layers of cuticle separated by air gaps. Here we describe a biological pattern of surface functionality that we have found in these photonic structures. This pattern is a gradient of surface polarity of the ridge structures that runs from their polar tops to their less-polar bottoms. This finding shows a biological pattern design that could stimulate numerous technological applications ranging from photonic security tags to self-cleaning surfaces, gas separators, protective clothing, sensors, and many others. As an important first step, this biomaterial property and our knowledge of its basis has allowed us to unveil a general mechanism of selective vapor response observed in the photonic Morpho nanostructures. This mechanism of selective vapor response brings a multivariable perspective for sensing, where selectivity is achieved within a single chemically graded nanostructured sensing unit, rather than from an array of separate sensors.Structural colors in tropical butterflies have been of scientific interest for almost a century (1, 2), with many optical studies examining Morpho species (3, 4). The iridescence exhibited by scales of Morpho butterflies originates from 3D vertical ridge structures of stacked periodic layers of cuticle separated by air gaps (5).In this study, we have found a biological pattern of surface functionality within these ridge structures of Morpho scales. This pattern is a naturally formed gradient of surface polarity extending from the polar tops of ridges to their less-polar bottoms. We validated the existence of this gradient by applying a suite of complementary techniques to assess the chemistry of the ridges on the nanoscale. At first, we mapped the spatial polarity distribution of individual ridges by staining scales with polarity-sensitive dyes and performing spatially resolved optical characterization experiments. We further monitored the change of spatial polarity distribution within individual ridges before and after a control experiment aimed to reduce this initial polarity gradient. Finally, we performed detailed experiments of exposing Morpho scales to vapors of different polarity, observed the optical spectral responses, and compared these experimental effects with responses from simulated Morpho nanostructures with either a uniform or a gradient surface polarity. Results of these complementary techniques provided strong evidence of the existence of the naturally formed gradient of surface polarity on the ridges of Morpho scales.Although this surface polarity gradient may not be essential for butterfly survival, but rather is a by-product of the process of scale development, this perspective on biological pattern design can offer opportunities for a variety of technological applications. Examples of such applications include photonic security tags, self-cleaning surfaces, gas separators, protective clothing, sensors, and many others. As a first application, the knowledge of the gradient of surface polarity of the ridges allowed us to unveil a general mechanism of selective vapor response in photonic Morpho nanostructures. According to this mechanism, vapors of different polarity are preferentially adsorbed onto the respective regions of the ridges. This preferential adsorption is expressed in the corresponding spectral regions of the reflectance spectra. Our previous work on the vapor response of Morpho butterfly scales (6) did not provide a mechanism for the observed unusually selective vapor response.In vapor sensing, the quest for selective sensors started in the 1950s with studies of metal oxides (7). Following initial observations of vapor responses of different materials, competing requirements between selectivity and reversibility of sensors were discovered, explaining poor selectivity of individual sensors (8). The idea of combining individual sensors into arrays (9) became an accepted compromise to improve selectivity. At present, development of selectivity-tunable yet simplified sensor systems attracts tremendous attention (10, 11). The mechanism of selective vapor response reported here introduces a different perspective for selective vapor sensing, where the selectivity is achieved within a single chemically graded nanostructured sensing unit, rather than from an array of separate sensors.     

Complete nucleotide analysis of the structural genome of the infectious bronchitis virus strain md27 reveals its mosaic nature

Infectious bronchitis virus (IBV) causes highly contagious respiratory or urogenital tract diseases in chickens. The Maryland 27(Md27) strain was first isolated in 1976 from diseased chicken flocks in the Delmarva Peninsula region. To understand the genetic diversity and phylogenetic relationship of existing strains with Md27, the complete nucleotide sequence of the 3'end coding region (～7.2 kb) of Md27 was determined and compared with other IBV strains and coronaviruses. It has the same S-3-M-5-N-3' gene order, as is the case of other IBV strains. The spike gene of Md27 exhibits 97% identity with the SE17 strain. There are deletions at the spike gene, non-coding region between M and 5 genes, and at the 3' untranslated region (UTR), which is different from Ark-like strains. Phylogenetic analysis and sequence alignments demonstrate that Md27 is a chimera containing different gene segments that are most closely related to the SE17, Conn and JMK strains. This current study provides evidence for genomic mutations and intergenic recombination that have taken place in the evolution of IBV strain Md27.     

Cilia in children with recurrent upper respiratory tract infections: ultrastructural observations.

We investigated the ultrastructure of nasal cilia in 27 children suffering from recurrent infections of the upper respiratory tract, during and after the onset of an acute respiratory infection, and after a convalescent period of 12 weeks. Our results demonstrated that in seven subjects after resolution of infection, the morphology of a large proportion of the cilia (32%) was not back to normal. These findings suggest a long-term residual effect of infection, or the inability to reestablish normal ciliary structure during the convalescent period in some subjects with recurrent upper respiratory tract infection.     

Prediction and experimental validation of enzyme substrate specificity in protein structures

Structural Genomics aims to elucidate protein structures to identify their functions. Unfortunately, the variation of just a few residues can be enough to alter activity or binding specificity and limit the functional resolution of annotations based on sequence and structure; in enzymes, substrates are especially difficult to predict. Here, large-scale controls and direct experiments show that the local similarity of five or six residues selected because they are evolutionarily important and on the protein surface can suffice to identify an enzyme activity and substrate. A motif of five residues predicted that a previously uncharacterized Silicibacter sp. protein was a carboxylesterase for short fatty acyl chains, similar to hormone-sensitive-lipase–like proteins that share less than 20% sequence identity. Assays and directed mutations confirmed this activity and showed that the motif was essential for catalysis and substrate specificity. We conclude that evolutionary and structural information may be combined on a Structural Genomics scale to create motifs of mixed catalytic and noncatalytic residues that identify enzyme activity and substrate specificity.As the list of known genes grows exponentially, the elucidation of their function remains a major bottleneck and lags far behind the production of sequences (1–5). The best approach remains to search computationally for functionally characterized sequence homologs, ideally with greater than 50% sequence identity (6). Binding specificity, however, is sensitive to subtle amino acid differences, and the transfer of substrate between related enzymes is prone to errors when sequence identity is below 65–80% (7–9). These thresholds vary from case to case: Some orthologs will maintain identical functions down to 25% sequence identify (9), whereas paralogs can take on highly diverse activities (10). Other difficulties that plague annotation transfer between homologs are that individual small molecules may each bind to multiple and distinct molecular pockets (11), that different residues can support similar chemistries (12), and that activity can vary even when catalytic residues are conserved (13–18). To raise annotation accuracy, Structural Genomics (19) made structural information widely available and spurred the development of annotation methods dependent on local chemical and physical environments (20), sequence and structural comparisons (21), or 3D templates (22). In the case of the latter, these methods search between proteins for local structural similarities over a few signature residues that represent the telltale parts of a functional site, so-called “3D templates” (3, 14, 18, 22–24). The residue composition of 3D templates is critical, however, and derived from experiments (25) or from analyses of functional sites and determinants (14, 15, 26). The sensitivity and specificity of template-based annotations still needs to be established experimentally (27, 28), but retrospective controls suggest they often predict enzyme catalytic activity (14, 16, 17, 29, 30).Here, to extend the functional resolution of 3D template annotations to substrates, we exploit Evolutionary Tracing (ET) (31, 32). ET ranks sequence positions by the tendency of their evolutionary variations to correlate with major or with minor divergences. Top-ranked ET sequence positions are the most evolutionarily and, presumably, functionally important, and indeed they map out functional sites and specificity determinants (33) accurately enough to efficiently design mutations that block or swap functions among homologs in vitro (34–36) or in vivo (37, 38).Accordingly, given a query protein of unknown function, the ET Annotation pipeline (ETA) builds a 3D template from five or six top-ranked ET residues that also cluster together on surface regions of protein structures (31, 32). ETA then searches already annotated protein structures, the targets, for those that match the query 3D template (Fig. 1 and Movie S1). False positive matches are common but can be recognized because they typically (i) involve unimportant residues in the target (39), (ii) are not reciprocated back to the query (40), and (iii) point to multiple proteins that each bear unrelated functions. With appropriate specificity filters to eliminate these false positives, ETA identified enzyme activity down to the first three Enzyme Commission (EC) levels with 92% accuracy (40), as well as in nonenzymes (41) in large-scale Structural Genomics retrospective controls. The prediction of substrate specificity remains an open question and further requires accurate identification of the fourth and last EC level (42) presumably by adding a more discriminating use of 3D template residues than is sufficient to specify a general chemical process (43). Some sequence methods (29, 30) and other structure methods (14, 44) have aimed to predict all four EC levels, but to our knowledge they have not been directly tested on de novo predictions of substrate specificity.Open in a separate windowFig. 1.ETA accurately determines substrate specificity. (A) The ET algorithm is applied to a protein from Sulfolobus tokadaii strain 7 (green, PDB ID code 2eer, chain A) to identify evolutionarily important residues. A cluster of 10 or more important residues is identified and a Template Picker algorithm further selects five or six residues to act as a template that is used to probe a target library of proteins with known functions. Paired-distance matching algorithm identifies regions in protein structures in the target library that are similar to the template. Found matches are next passed to the SVM, which identifies significant matches based on geometric and evolutionary similarities. ETA repeats all these steps reciprocally, generating templates from target structures and searching for matches in the query protein. Following this protocol, ETA suggests four matches: alcohol dehydrogenase from Saccharomyces cerevisae (blue left, PDB ID code 2hcy), alcohol dehydrogenase from S. solfataricus (blue middle, PDB ID code 1r37), human class II alcohol dehydrogenase (blue right, PDB ID code 3cos), and NADP(H)-dependent cinnamyl alcohol dehydrogenase from S. cerevisae (red, PDB ID code 1piw) to the query protein. (B) The most seen function among matches, alcohol dehydrogenase activity (EC 1.1.1.1), is identified with high confidence with a confidence value of 1.125 as calculated in the box. (C) Comparison of PPV versus confidence score binned at <1, =1, and >1 for both six-residue templates (Left) and five-residue templates (Right) when considering only matches of <30% sequence identity. For more detail, see Fig. S1. (D) Comparison of PPV when predictions are made using ETA or the closest structural match (TM-align). Horizontal axis shows the maximum sequence identity of matches for proteins depicted in corresponding bars; the vertical axis is the PPV for each bin range.In this study, we improve the functional resolution of the ETA pipeline to identify relevant functional homology down to very low sequence identity and add substrate specificity to its large-scale predictions. We then experimentally validate the predictions and show that both catalytic and noncatalytic residues are essential for 3D templates to pinpoint activity and substrate specificity.     

Stoichiometry of molecular complexes at adhesions in living cells

We describe a method to detect molecular complexes and measure their stoichiometry in living cells from simultaneous fluctuations of the fluorescence intensity in two image channels, each detecting a different kind of protein. The number and brightness (N&B) analysis, namely, the use of the ratio between the variance and the average intensity to obtain the brightness of molecules, is extended to the cross-variance of the intensity fluctuations in two channels. We apply the cross-variance method to determine the stoichiometry of complexes containing paxillin and vinculin or focal adhesion kinase (FAK) in disassembling adhesions in mouse embryo fibroblasts expressing FAK, vinculin, and paxillin-tagged with EGFP and mCherry. We found no complexes of these proteins in the cytoplasm away from the adhesions. However, at the adhesions, large aggregates leave, forming a hole, during their disassembly. This hole shows cross-correlation between FAK and paxillin and vinculin and paxillin. From the amplitude of the correlated fluctuations we determine the composition of the aggregates leaving the adhesions. These aggregates disassemble rapidly in the cytoplasm because large complexes are found only in very close proximity to the adhesions or at their borders.     

Kinetics of nucleotide-dependent structural transitions in the kinesin-1 hydrolysis cycle

To dissect the kinetics of structural transitions underlying the stepping cycle of kinesin-1 at physiological ATP, we used interferometric scattering microscopy to track the position of gold nanoparticles attached to individual motor domains in processively stepping dimers. Labeled heads resided stably at positions 16.4 nm apart, corresponding to a microtubule-bound state, and at a previously unseen intermediate position, corresponding to a tethered state. The chemical transitions underlying these structural transitions were identified by varying nucleotide conditions and carrying out parallel stopped-flow kinetics assays. At saturating ATP, kinesin-1 spends half of each stepping cycle with one head bound, specifying a structural state for each of two rate-limiting transitions. Analysis of stepping kinetics in varying nucleotides shows that ATP binding is required to properly enter the one-head–bound state, and hydrolysis is necessary to exit it at a physiological rate. These transitions differ from the standard model in which ATP binding drives full docking of the flexible neck linker domain of the motor. Thus, this work defines a consensus sequence of mechanochemical transitions that can be used to understand functional diversity across the kinesin superfamily.Kinesin-1 is a motor protein that steps processively toward microtubule plus-ends, tracking single protofilaments and hydrolyzing one ATP molecule per step (1–6). Step sizes corresponding to the tubulin dimer spacing of 8.2 nm are observed when the molecule is labeled by its C-terminal tail (7–10) and to a two-dimer spacing of 16.4 nm when a single motor domain is labeled (4, 11, 12), consistent with the motor walking in a hand-over-hand fashion. Kinesin has served as an important model system for advancing single-molecule techniques (7–10) and is clinically relevant for its role in neurodegenerative diseases (13), making dissection of its step a popular ongoing target of study.Despite decades of work, many essential components of the mechanochemical cycle remain disputed, including (i) how much time kinesin-1 spends in a one-head–bound (1HB) state when stepping at physiological ATP concentrations, (ii) whether the motor waits for ATP in a 1HB or two-heads–bound (2HB) state, and (iii) whether ATP hydrolysis occurs before or after tethered head attachment (4, 11, 14–20). These questions are important because they are fundamental to the mechanism by which kinesins harness nucleotide-dependent structural changes to generate mechanical force in a manner optimized for their specific cellular tasks. Addressing these questions requires characterizing a transient 1HB state in the stepping cycle in which the unattached head is located between successive binding sites on the microtubule. This 1HB intermediate is associated with the force-generating powerstroke of the motor and underlies the detachment pathway that limits motor processivity. Optical trapping (7, 19, 21, 22) and single-molecule tracking studies (4, 8–11) have failed to detect this 1HB state during stepping. Single-molecule fluorescence approaches have detected a 1HB intermediate at limiting ATP concentrations (11, 12, 14, 15), but apart from one study that used autocorrelation analysis to detect a 3-ms intermediate (17), the 1HB state has been undetectable at physiological ATP concentrations.Single-molecule microscopy is a powerful tool for studying the kinetics of structural changes in macromolecules (23). Tracking steps and potential substeps for kinesin-1 at saturating ATP has until now been hampered by the high stepping rates of the motor (up to 100 s⁻¹), which necessitates high frame rates, and the small step size (8.2 nm), which necessitates high spatial precision (7). Here, we apply interferometric scattering microscopy (iSCAT), a recently established single-molecule tool with high spatiotemporal resolution (24–27) to directly visualize the structural changes underlying kinesin stepping. By labeling one motor domain in a dimeric motor, we detect a 1HB intermediate state in which the tethered head resides over the bound head for half the duration of the stepping cycle at saturating ATP. We further show that at physiological stepping rates, ATP binding is required to enter this 1HB state and that ATP hydrolysis is required to exit it. This work leads to a significant revision of the sequence and kinetics of mechanochemical transitions that make up the kinesin-1 stepping cycle and provides a framework for understanding functional diversity across the kinesin superfamily.     

Chemical and Structural Analysis of Newly Prepared Co-W-Al Alloy by Aluminothermic Reaction

This article is devoted to the characterization of a new Co-W-Al alloy prepared by an aluminothermic reaction. This alloy is used for the subsequent preparation of a special composite nanopowder and for the surface coating of aluminum, magnesium, or iron alloys. Due to the very high temperature (2000 °C–3000 °C) required for the reaction, thermite was added to the mixture. Pulverized coal was also added in order to obtain the appropriate metal carbides (Co, W, Ti), which increase hardness, resistance to abrasion, and the corrosion of the coating and have good high temperature properties. The phase composition of the alloy prepared by the aluminothermic reaction showed mainly cobalt, tungsten, and aluminum, as well as small amounts of iron, titanium, and calcium. No carbon was identified using this method. The microstructure of this alloy is characterized by a cobalt matrix with smaller regular and irregular carbide particles doped by aluminum.     

Preservation of human liver grafts in UW solution. Ultrastructural evidence for endothelial and Kupffer cell activation during cold ischemia and after ischemia-reperfusion

Abstract: Biopsies taken from 13 human liver grafts at different stages of the transplantation process were used for study of the morphology of sinusoidal cells prior to harvesting (5 biopsies), after preservation in UW solution (10 biopsies), and after complete revascularization (13 biopsies). The mean cold ischemic period was 12 h 30. Immediate follow up was uneventful and the mean peak of post-operative transaminases below 1300 IU/1. Biopsies were perfusion-fixed by the transparenchymal route to ensure satisfactory ultrastructural results. There were no loose sinusoidal endothelial cells in the lumen and no signs of cellular death. Some endothelial cells presented signs of activation at the end of the preservation period, and even more after revascularization, with numerous lucent vacuoles resembling endosomes in the cytoplasm. Kupffer cells also presented signs of activation, particularly after reperfusion. The retraction of endothelial cell processes which formed large gaps during cold ischemia proved to be partly reversible after reperfusion. Signs of endothelial cell damage with gaps and partial rupture of the plasmic membrane were also observed, particularly after revascularization, in areas which contained numerous inflammatory cells adhering to the wall. The Disse space was not generally enlarged and contained no inflammatory cells. The sinusoidal pole of hepatocytes was occasionally damaged with the formation of blebs. These results strongly suggest that any drug or perservation solution that will inhibit endothelial and Kupffer cell activation could be beneficial in the prevention of preservation and reperfusion injury.     

On the dynamical nature of the active center in a single-site photocatalyst visualized by 4D ultrafast electron microscopy

Understanding the dynamical nature of the catalytic active site embedded in complex systems at the atomic level is critical to developing efficient photocatalytic materials. Here, we report, using 4D ultrafast electron microscopy, the spatiotemporal behaviors of titanium and oxygen in a titanosilicate catalytic material. The observed changes in Bragg diffraction intensity with time at the specific lattice planes, and with a tilted geometry, provide the relaxation pathway: the Ti⁴⁺=O²⁻ double bond transformation to a Ti³⁺−O¹⁻ single bond via the individual atomic displacements of the titanium and the apical oxygen. The dilation of the double bond is up to 0.8 Å and occurs on the femtosecond time scale. These findings suggest the direct catalytic involvement of the Ti³⁺−O¹⁻ local structure, the significance of nonthermal processes at the reactive site, and the efficient photo-induced electron transfer that plays a pivotal role in many photocatalytic reactions.Single-site catalysts of both the thermally and photoactivated kind now occupy a prominent place in industrial- and laboratory-scale heterogeneous catalysis (1–8). Among the most versatile of these are the ones consisting of coordinatively unsaturated transition metal ions (Ti, Cr, Fe, Mn…) that occupy substitutional sites in well-defined, three-dimensionally extended, open-structure silicates of the zeolite type. The well-known and most widely used are the 4- or 5-coordinated Ti(IV) ions accommodated within the crystalline phase of silica, silicalite (9–14).Titanosilicates, especially, are used extensively both industrially and in the laboratory for a wide range of chemo-, regio-, and shape-selective oxidations of organic compounds (15–18). These single-site heterogeneous photocatalysts are quite distinct from those typified by TiO₂, SrTiO₃, and other titaniferous photocatalysts where the Ti(IV) ions are in 6-coordination; and where, in interpreting the processes involved in harnessing solar radiation, electronic band structure considerations hold sway in preference to the localized states (see, e.g., refs. 19, 20). It has been demonstrated (16–18, 21, 22) that single-site, coordinatively unsaturated Ti(IV)-centered photocatalysts are especially useful in the aerial oxidation of environmental pollutants in the photodegradation of NO (to N₂ and O₂), of H₂O (to H₂ and O₂), and in the photocatalytic reduction of CO₂ to yield methanol. There is an exigent need to explore the precise nature of the electronic, temporal, and spatial changes accompanying the initial act of photoabsorption that sets in train the ensuing elementary chemical processes that are of vital environmental significance in, for example, the utilization of anthropogenic CO₂ as a chemical feedstock (23).Here, we report the use of 4D ultrafast electron microscopy (UEM) (24–26) to trace the spatiotemporal behavior of the Ti(IV) and O²⁻ ions at the photocatalytic active center in the structurally well-characterized titanosilicate Na₄Ti₂Si₈O₂₂·4H₂O, known as JDF-L1 (27–29). JDF stands for Jilin–Davy–Faraday, as the crystalline solid described here was discovered and characterized in joint work involving Jilin University (P. R. China) and the Davy–Faraday Laboratory at the Royal Institution of Great Britain. L1 stands for the first layered catalyst formed during that collaboration; 5-coordinated solids containing Ti(IV) ions are rare among the hundred or so titaniferous minerals, the prime example being fresnoite, Ba₂Ti₂Si₂O₈. We choose this photocatalyst with 5-coordinated Ti because of its unique bonding structure. Our approach entails monitoring, at femtosecond resolution, the changes in intensities and anisotropies of Bragg (electron) diffraction reflections in such a manner as to retrieve the change in valency and the time scales involved in both the formation of Ti³⁺−O¹⁻ bond and the relaxation of the energy back to the local structure of the Ti = O bond in JDF-L1. Through these diffraction studies, and the associated Debye–Waller effect and structural factors anisotropies, it is found that a Ti³⁺−O¹⁻ bond is formed on the femtosecond time scale; whereas, the back relaxation from the site to the structure occurs on a much longer time scale, permitting ample time for reactivity involving Ti³⁺−O¹⁻, and indicating the potential significance of nonthermal processes in the photocatalytic activity at the reactive site.     

Conserved patterns of protein interaction in multiple species

To elucidate cellular machinery on a global scale, we performed a multiple comparison of the recently available protein-protein interaction networks of Caenorhabditis elegans, Drosophila melanogaster, and Saccharomyces cerevisiae. This comparison integrated protein interaction and sequence information to reveal 71 network regions that were conserved across all three species and many exclusive to the metazoans. We used this conservation, and found statistically significant support for 4,645 previously undescribed protein functions and 2,609 previously undescribed protein interactions. We tested 60 interaction predictions for yeast by two-hybrid analysis, confirming approximately half of these. Significantly, many of the predicted functions and interactions would not have been identified from sequence similarity alone, demonstrating that network comparisons provide essential biological information beyond what is gleaned from the genome.     

Rapid structural change in synaptosomal-associated protein 25 (SNAP25) precedes the fusion of single vesicles with the plasma membrane in live chromaffin cells

The SNARE complex consists of the three proteins synaptobrevin-2, syntaxin, and synaptosomal-associated protein 25 (SNAP25) and is thought to execute a large conformational change as it drives membrane fusion and exocytosis. The relation between changes in the SNARE complex and fusion pore opening is, however, still unknown. We report here a direct measurement relating a change in the SNARE complex to vesicle fusion on the millisecond time scale. In individual chromaffin cells, we tracked conformational changes in SNAP25 by total internal reflection fluorescence resonance energy transfer (FRET) microscopy while exocytotic catecholamine release from single vesicles was simultaneously recorded using a microfabricated electrochemical detector array. A local rapid and transient FRET change occurred precisely where individual vesicles released catecholamine. To overcome the low time resolution of the imaging frames needed to collect sufficient signal intensity, a method named event correlation microscopy was developed, which revealed that the FRET change was abrupt and preceded the opening of an exocytotic fusion pore by ∼90 ms. The FRET change correlated temporally with the opening of the fusion pore and not with its dilation.