N terminus of ASPP2 binds to Ras and enhances Ras/Raf/MEK/ERK activation to promote oncogene-induced senescence

The ASPP2 (also known as 53BP2L) tumor suppressor is a proapoptotic member of a family of p53 binding proteins that functions in part by enhancing p53-dependent apoptosis via its C-terminal p53-binding domain. Mounting evidence also suggests that ASPP2 harbors important nonapoptotic p53-independent functions. Structural studies identify a small G protein Ras-association domain in the ASPP2 N terminus. Because Ras-induced senescence is a barrier to tumor formation in normal cells, we investigated whether ASPP2 could bind Ras and stimulate the protein kinase Raf/MEK/ERK signaling cascade. We now show that ASPP2 binds to Ras–GTP at the plasma membrane and stimulates Ras-induced signaling and pERK1/2 levels via promoting Ras–GTP loading, B-Raf/C-Raf dimerization, and C-Raf phosphorylation. These functions require the ASPP2 N terminus because BBP (also known as 53BP2S), an alternatively spliced ASPP2 isoform lacking the N terminus, was defective in binding Ras–GTP and stimulating Raf/MEK/ERK signaling. Decreased ASPP2 levels attenuated H-RasV12–induced senescence in normal human fibroblasts and neonatal human epidermal keratinocytes. Together, our results reveal a mechanism for ASPP2 tumor suppressor function via direct interaction with Ras–GTP to stimulate Ras-induced senescence in nontransformed human cells.ASPP2, also known as 53BP2L, is a tumor suppressor whose expression is altered in human cancers (1). Importantly, targeting of the ASPP2 allele in two different mouse models reveals that ASPP2 heterozygous mice are prone to spontaneous and γ-irradiation–induced tumors, which rigorously demonstrates the role of ASPP2 as a tumor suppressor (2, 3). ASPP2 binds p53 via the C-terminal ankyrin-repeat and SH3 domain (4–6), is damage-inducible, and can enhance damage-induced apoptosis in part through a p53-mediated pathway (1, 2, 7–10). However, it remains unclear what biologic pathways and mechanisms mediate ASPP2 tumor suppressor function (1). Indeed, accumulating evidence demonstrates that ASPP2 also mediates nonapoptotic p53-independent pathways (1, 3, 11–15).The induction of cellular senescence forms an important barrier to tumorigenesis in vivo (16–21). It is well known that oncogenic Ras signaling induces senescence in normal nontransformed cells to prevent tumor initiation and maintain complex growth arrest pathways (16, 18, 21–24). The level of oncogenic Ras activation influences its capacity to activate senescence; high levels of oncogenic H-RasV12 signaling leads to low grade tumors with senescence markers, which progress to invasive cancers upon senescence inactivation (25). Thus, tight control of Ras signaling is critical to ensure the proper biologic outcome in the correct cellular context (26–28).The ASPP2 C terminus is important for promoting p53-dependent apoptosis (7). The ASPP2 N terminus may also suppress cell growth (1, 7, 29–33). Alternative splicing can generate the ASPP2 N-terminal truncated protein BBP (also known as 53BP2S) that is less potent in suppressing cell growth (7, 34, 35). Although the ASPP2 C terminus mediates nuclear localization, full-length ASPP2 also localizes to the cytoplasm and plasma membrane to mediate extranuclear functions (7, 11, 12, 36). Structural studies of the ASPP2 N terminus reveal a β–Grasp ubiquitin-like fold as well as a potential Ras-binding (RB)/Ras-association (RA) domain (32). Moreover, ASPP2 can promote H-RasV12–induced senescence (13, 15). However, the molecular mechanism(s) of how ASPP2 directly promotes Ras signaling are complex and remain to be completely elucidated.Here, we explore the molecular mechanisms of how Ras-signaling is enhanced by ASPP2. We demonstrate that ASPP2: (i) binds Ras-GTP and stimulates Ras-induced ERK signaling via its N-terminal domain at the plasma membrane; (ii) enhances Ras-GTP loading and B-Raf/C-Raf dimerization and forms a ASPP2/Raf complex; (iii) stimulates Ras-induced C-Raf phosphorylation and activation; and (iv) potentiates H-RasV12–induced senescence in both primary human fibroblasts and neonatal human epidermal keratinocytes. These data provide mechanistic insight into ASPP2 function(s) and opens important avenues for investigation into its role as a tumor suppressor in human cancer.     

A family of starch-active polysaccharide monooxygenases

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

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

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

The evolution of self-control

Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.Since Darwin, understanding the evolution of cognition has been widely regarded as one of the greatest challenges for evolutionary research (1). Although researchers have identified surprising cognitive flexibility in a range of species (2–40) and potentially derived features of human psychology (41–61), we know much less about the major forces shaping cognitive evolution (62–71). With the notable exception of Bitterman’s landmark studies conducted several decades ago (63, 72–74), most research comparing cognition across species has been limited to small taxonomic samples (70, 75). With limited comparable experimental data on how cognition varies across species, previous research has largely relied on proxies for cognition (e.g., brain size) or metaanalyses when testing hypotheses about cognitive evolution (76–92). The lack of cognitive data collected with similar methods across large samples of species precludes meaningful species comparisons that can reveal the major forces shaping cognitive evolution across species, including humans (48, 70, 89, 93–98).To address these challenges we measured cognitive skills for self-control in 36 species of mammals and birds (Fig. 1 and Tables S1–S4) tested using the same experimental procedures, and evaluated the leading hypotheses for the neuroanatomical underpinnings and ecological drivers of variance in animal cognition. At the proximate level, both absolute (77, 99–107) and relative brain size (108–112) have been proposed as mechanisms supporting cognitive evolution. Evolutionary increases in brain size (both absolute and relative) and cortical reorganization are hallmarks of the human lineage and are believed to index commensurate changes in cognitive abilities (52, 105, 113–115). Further, given the high metabolic costs of brain tissue (116–121) and remarkable variance in brain size across species (108, 122), it is expected that the energetic costs of large brains are offset by the advantages of improved cognition. The cortical reorganization hypothesis suggests that selection for absolutely larger brains—and concomitant cortical reorganization—was the predominant mechanism supporting cognitive evolution (77, 91, 100–106, 120). In contrast, the encephalization hypothesis argues that an increase in brain volume relative to body size was of primary importance (108, 110, 111, 123). Both of these hypotheses have received support through analyses aggregating data from published studies of primate cognition and reports of “intelligent” behavior in nature—both of which correlate with measures of brain size (76, 77, 84, 92, 110, 124).Open in a separate windowFig. 1.A phylogeny of the species included in this study. Branch lengths are proportional to time except where long branches have been truncated by parallel diagonal lines (split between mammals and birds ∼292 Mya).With respect to selective pressures, both social and dietary complexities have been proposed as ultimate causes of cognitive evolution. The social intelligence hypothesis proposes that increased social complexity (frequently indexed by social group size) was the major selective pressure in primate cognitive evolution (6, 44, 48, 50, 87, 115, 120, 125–141). This hypothesis is supported by studies showing a positive correlation between a species’ typical group size and the neocortex ratio (80, 81, 85–87, 129, 142–145), cognitive differences between closely related species with different group sizes (130, 137, 146, 147), and evidence for cognitive convergence between highly social species (26, 31, 148–150). The foraging hypothesis posits that dietary complexity, indexed by field reports of dietary breadth and reliance on fruit (a spatiotemporally distributed resource), was the primary driver of primate cognitive evolution (151–154). This hypothesis is supported by studies linking diet quality and brain size in primates (79, 81, 86, 142, 155), and experimental studies documenting species differences in cognition that relate to feeding ecology (94, 156–166).Although each of these hypotheses has received empirical support, a comparison of the relative contributions of the different proximate and ultimate explanations requires (i) a cognitive dataset covering a large number of species tested using comparable experimental procedures; (ii) cognitive tasks that allow valid measurement across a range of species with differing morphology, perception, and temperament; (iii) a representative sample within each species to obtain accurate estimates of species-typical cognition; (iv) phylogenetic comparative methods appropriate for testing evolutionary hypotheses; and (v) unprecedented collaboration to collect these data from populations of animals around the world (70).Here, we present, to our knowledge, the first large-scale collaborative dataset and comparative analysis of this kind, focusing on the evolution of self-control. We chose to measure self-control—the ability to inhibit a prepotent but ultimately counterproductive behavior—because it is a crucial and well-studied component of executive function and is involved in diverse decision-making processes (167–169). For example, animals require self-control when avoiding feeding or mating in view of a higher-ranking individual, sharing food with kin, or searching for food in a new area rather than a previously rewarding foraging site. In humans, self-control has been linked to health, economic, social, and academic achievement, and is known to be heritable (170–172). In song sparrows, a study using one of the tasks reported here found a correlation between self-control and song repertoire size, a predictor of fitness in this species (173). In primates, performance on a series of nonsocial self-control control tasks was related to variability in social systems (174), illustrating the potential link between these skills and socioecology. Thus, tasks that quantify self-control are ideal for comparison across taxa given its robust behavioral correlates, heritable basis, and potential impact on reproductive success.In this study we tested subjects on two previously implemented self-control tasks. In the A-not-B task (27 species, n = 344), subjects were first familiarized with finding food in one location (container A) for three consecutive trials. In the test trial, subjects initially saw the food hidden in the same location (container A), but then moved to a new location (container B) before they were allowed to search (Movie S1). In the cylinder task (32 species, n = 439), subjects were first familiarized with finding a piece of food hidden inside an opaque cylinder. In the following 10 test trials, a transparent cylinder was substituted for the opaque cylinder. To successfully retrieve the food, subjects needed to inhibit the impulse to reach for the food directly (bumping into the cylinder) in favor of the detour response they had used during the familiarization phase (Movie S2).Thus, the test trials in both tasks required subjects to inhibit a prepotent motor response (searching in the previously rewarded location or reaching directly for the visible food), but the nature of the correct response varied between tasks. Specifically, in the A-not-B task subjects were required to inhibit the response that was previously successful (searching in location A) whereas in the cylinder task subjects were required to perform the same response as in familiarization trials (detour response), but in the context of novel task demands (visible food directly in front of the subject).     

Aggregation propensities of superoxide dismutase G93 hotspot mutants mirror ALS clinical phenotypes

Protein framework alterations in heritable Cu, Zn superoxide dismutase (SOD) mutants cause misassembly and aggregation in cells affected by the motor neuron disease ALS. However, the mechanistic relationship between superoxide dismutase 1 (SOD1) mutations and human disease is controversial, with many hypotheses postulated for the propensity of specific SOD mutants to cause ALS. Here, we experimentally identify distinguishing attributes of ALS mutant SOD proteins that correlate with clinical severity by applying solution biophysical techniques to six ALS mutants at human SOD hotspot glycine 93. A small-angle X-ray scattering (SAXS) assay and other structural methods assessed aggregation propensity by defining the size and shape of fibrillar SOD aggregates after mild biochemical perturbations. Inductively coupled plasma MS quantified metal ion binding stoichiometry, and pulsed dipolar ESR spectroscopy evaluated the Cu²⁺ binding site and defined cross-dimer copper–copper distance distributions. Importantly, we find that copper deficiency in these mutants promotes aggregation in a manner strikingly consistent with their clinical severities. G93 mutants seem to properly incorporate metal ions under physiological conditions when assisted by the copper chaperone but release copper under destabilizing conditions more readily than the WT enzyme. Altered intradimer flexibility in ALS mutants may cause differential metal retention and promote distinct aggregation trends observed for mutant proteins in vitro and in ALS patients. Combined biophysical and structural results test and link copper retention to the framework destabilization hypothesis as a unifying general mechanism for both SOD aggregation and ALS disease progression, with implications for disease severity and therapeutic intervention strategies.ALS is a lethal degenerative disease of the human motor system (1). Opportunities for improved understanding and clinical intervention arose from the discovery that up to 23.5% of familial ALS cases and 7% of spontaneous cases are caused by mutations in the superoxide dismutase 1 (SOD1) gene encoding human Cu, Zn SOD (2–4). SOD is a highly conserved (5), dimeric, antioxidant metalloenzyme that detoxifies superoxide radicals (6, 7), but overexpression of SOD1 ALS mutants is sufficient to cause disease in mice (8). Misfolded and/or aggregated SOD species are deposited within mouse neuronal and glial inclusions (9, 10), even before symptoms appear (11, 12). Although human familial ALS has a symptomatic phenotype indistinguishable from sporadic cases (13), individual SOD1 mutations can result in highly variable disease progression and penetrance (14, 15).Many nongeneral mechanisms, including loss of activity or gain of function, were postulated to explain the roles of SOD mutants in ALS (3, 16–19). Recently, however, an initial hypothesis proposing that SOD manifests disease symptoms by framework destabilization (protein instability caused by structural defects) and consequent protein misassembly and aggregation has gained renewed support (2, 10, 14, 20–23). Ironically, WT SOD is an unusually stable protein (7, 24–26), and precisely how SOD mutations cause disease remains unclear. For instance, human SOD free cysteine residues C6 and C111 have been implicated in protein aggregation by promoting cross-linking (27, 28) and/or stability changes associated with oxidative modifications (29–33). Mutation of the chemically reactive thiols significantly decreases the irreversible denaturation rate for human and bovine SOD (24, 34). However, ALS mutants in a C6A/C111S SOD (AS-SOD) background (35, 36) maintain the native C57–C146 disulfide bond but can still undergo aggregation, and mutations of the free cysteines can cause ALS (37, 38). These results imply that free cysteines are not strictly required but rather, may alter aggregation kinetics (20). SOD also contains two metal ion cofactors in each subunit: a catalytic copper ion (6) and a structurally stabilizing zinc ion (34, 39, 40) (Fig. 1A). In higher eukaryotes, a copper chaperone for SOD (CCS) plays an important role in catalyzing both the copper incorporation and native disulfide bond formation (41). Structural analyses of apo WT SOD point to greater flexibility or increased solvent accessibility of C6 otherwise buried in the stable dimer interface (42, 43), and molecular dynamics simulations also suggest a critical role for metal ions in protein structure, because SOD’s β-sheet propensity decreases in the absence of metals (44). As a result, apo SOD readily forms protein aggregates (45, 46), but the molecular structures of SOD aggregates are likely polymorphic and represent a controversial topic (23, 47–51). The intertwined effects of the aggregation-enhancing free cysteines, dimer-stabilizing metal ions, and CCS maturation of SOD complicate the study of the ALS-causing SOD mutations themselves, and therefore, a clear cause-and-effect relationship remains obscure and requires deconvolution.Open in a separate windowFig. 1.Comparison of crystallographic and solution structures of WT and G93A SOD. (A) Overall architecture of the WT SOD dimer is displayed in 90° rotated views. G93 (small red spheres) resides on a surface-exposed interstrand loop between the fifth and sixth sequential β-strands of SOD and is expected to be innocuous in facilitating protein stability; however, this site harbors the most substitutions observed to result in ALS. G93 is also distant from both (Upper) the dimer interface and (Lower Left) the SOD active site (gold and silver spheres), which are generally implicated as the major determinants for SOD stability. Small blue spheres denote free cysteines. (Lower Right) The close-up view of the mutation site (boxed region in Lower Left tilted forward) shows high similarity between WT (purple) and G93A (red) SOD crystal structures [Protein Data Bank ID codes 1PU0 (WT) and 2ZKY (G93A)]. Hydrogen bonds characteristic of a β-bulge motif are indicated, whereby G93 (or A93) represents position 1. The main chain carbonyl group of β-barrel cork residue L38 is adjacent to the G93 site. (B) SAXS-derived electron pair P(r) distributions from WT (purple) and G93A (red) SOD samples in solution are compared with the theoretical curve for 1PU0. P(r) plots are normalized to peak height. Ab initio models of WT SOD derived from P(r) data are depicted in purple, with crystal structure docked into mesh envelope. Contributions to major and minor peaks from subunit and dimer dimensions are indicated.To better understand the structural effects of ALS mutations on SOD architecture, we coupled the wealth of crystallographic knowledge on SOD structure (7, 52, 53) with small-angle X-ray scattering (SAXS) experiments to characterize misassembly aggregates of ALS mutant SODs in solution. Over 20 y ago, we solved the first atomic structure of the human WT SOD protein (Fig. 1A) (20, 34) and proposed the framework destabilization hypothesis to explain how diverse mutations located throughout the 153-residue β-barrel enzyme might produce a similar disease phenotype (2), albeit with distinctions in the progression trajectory. Since that time, a staggering number of ALS mutations has been documented in patients [178 (mostly missense) (54)], with a similar phenotype in dogs (55, 56). Solution-based techniques are increasingly being applied to connect structure to biological outcome, for instance, through examination of intermolecular interactions within stress-activated pathways, for instance (57, 58). SAXS, which can probe structures for a wide size range of species, also provides higher resolution insights (59), for instance, over visible light-scattering techniques, readily distinguishing unfolded from folded proteins (60).Here, we monitor the initial events of protein aggregation in a subset of ALS mutants localized to a mutational hotspot site at glycine 93. Specifically, we wished to test a possible structural basis for how G93 mutations (to A, C, D, R, S, or V) modulate age of onset and clinical severity in ALS patients (14, 15). The G93 substitution occurs in a β-bulge region (61) between sequential β-strands of the protein (Fig. 1A) on a protruding loop roughly ∼20 Å from T54, the nearest residue of the opposing subunit, and the metal-containing active site (Fig. S1). A priori, mutation of this outer loop position would not be expected to interfere with active site chemistry or buried molecular interfaces. However, we discovered correlations of aggregation nucleation kinetics of SOD proteins with ALS mutations at this site, the stabilizing effects of metal ion retention, and available data for clinical phenotypes in patients with the same mutation. Furthermore, by measuring and exploiting the dimer geometry to observe intrinsic SOD conformers, we show that G93 mutant proteins natively reveal increased intradimer conformational flexibility in the absence of aggregation, which may reflect an increased tendency for ALS mutants to become metal-deficient and misfolding-prone and further explain the correlation to disease severity. Collective results on G93 mutants, thus, support and extend the framework destabilization hypothesis.     

Regulation by a chaperone improves substrate selectivity during cotranslational protein targeting

The ribosome exit site is a crowded environment where numerous factors contact nascent polypeptides to influence their folding, localization, and quality control. Timely and accurate selection of nascent polypeptides into the correct pathway is essential for proper protein biogenesis. To understand how this is accomplished, we probe the mechanism by which nascent polypeptides are accurately sorted between the major cotranslational chaperone trigger factor (TF) and the essential cotranslational targeting machinery, signal recognition particle (SRP). We show that TF regulates SRP function at three distinct stages, including binding of the translating ribosome, membrane targeting via recruitment of the SRP receptor, and rejection of ribosome-bound nascent polypeptides beyond a critical length. Together, these mechanisms enhance the specificity of substrate selection into both pathways. Our results reveal a multilayered mechanism of molecular interplay at the ribosome exit site, and provide a conceptual framework to understand how proteins are selected among distinct biogenesis machineries in this crowded environment.Proper protein biogenesis is a prerequisite for the maintenance of a functional proteome. Accumulating data indicate that this process begins at the ribosome exit site, where many protein biogenesis machineries can interact and gain access to the nascent polypeptide. This includes chaperones (1–5) such as trigger factor (TF) (1, 4, 6, 7), Hsp70, and the nascent polypeptide-associated complex (8–13); modification enzymes (10, 14–16) such as N-acetyl transferase, methionine aminopeptidase, and arginyl transferase; protein-targeting and translocation machineries such as signal recognition particle (SRP) (17–20), SecA (21), the SecYEG (or Sec61p) (22, 23) and YidC translocases (24, 25), and the ribosome-bound quality control complex (26–30). Engagement of these factors with nascent polypeptides influences their folding, assembly, localization, processing, and quality control. Within seconds after the nascent polypeptide emerges from the ribosomal exit tunnel, it must engage the correct set of factors and thus commit to the proper biogenesis pathway. How this is accomplished in the crowded environment at the ribosome exit site is an emerging question. In this work, we address this question by deciphering how nascent proteins are selected between two major protein biogenesis machineries in bacteria, SRP and TF.SRP is a universally conserved ribonucleoprotein complex responsible for the cotranslational targeting of proteins to the eukaryotic endoplasmic reticulum (ER), or the bacterial plasma membrane (31). SRP recognizes ribosome-nascent chain complexes (termed RNC or cargo) carrying strong signal sequences and delivers them to the SecYEG or YidC translocation machinery on the target membrane. SRP binds RNC via two interactions: a helical N domain in the SRP54 protein (called Ffh in bacteria) binds the ribosomal protein L23, and a methionine-rich M domain binds hydrophobic signal sequences on nascent proteins as they emerge from the translating ribosome (Fig. 1A). Both SRP and SRP receptor (called FtsY in bacteria) also contain a conserved NG domain, comprised of a GTPase (guanosine 5′-triphosphate hydrolase) G domain and the N domain, whose direct interaction mediates the delivery of cargo to the target membrane.Open in a separate windowFig. 1.TF binds to SRP-occupied RNCs and weakens SRP binding. (A) Schematic depiction of the FRET assay to measure RNC–SRP binding. Green dot denotes Cm (donor); red dot denotes BODIPY FL (acceptor). (B) N-terminal sequences of the different substrates used in this study. Bold highlights the hydrophobic core of the signal sequences. Asterisk denotes the position where the amino acid is replaced by the Cm dye. (C and D) Equilibrium titrations for RNC–SRP binding in the presence of increasing TF concentration (indicated as increasing shades of red). The data were fitted to Eq. S2 and yielded the following parameters. (C) Apparent K_d values for RNC_FtsQ binding of 1.1 nM, 1.5 nM, 9.2 nM, and 16.6 nM and FRET end points of 0.54, 0.35, 0.29, and 0.17, respectively, with 0 µM, 1 µM, 5 µM, and 30 µM TF present. (D) Apparent K_d values for RNC_phoA binding of 17.2 nM, 21.1 nM, 30.3 nM, 28.3 nM, 31.5 nM, 104.5 nM, 106.3 nM, and 131.9 nM and FRET end points of 0.40, 0.41, 0.39, 0.29, 0.21, 0.19, 0.09, and 0.08, respectively, with 0 µM, 0.1 µM, 0.2 µM, 0.5 µM, 1 µM, 2 µM, 5 µM, and 10 µM TF present. (E) Summary of the effect of TF on apparent RNC–SRP binding affinity with the different substrates. The red dashed line denotes the cellular SRP concentration. Error bars are shown but may not be visible. Error bars are SDs from two to three measurements.Biophysical analyses (32–34) showed that membrane targeting is a two-step process in which SRP and FtsY first associate via their N domains to form a transient early intermediate (31, 32, 35). GTP (guanosine 5′-triphosphate)-driven rearrangements then bring the G domains of both proteins into close contact, giving a stable closed complex (36, 37). This rearrangement also exposes a membrane-binding helix of FtsY and thus is coupled to the membrane targeting of cargo (38). Importantly, SRP•FtsY assembly contributes extensively to the fidelity of SRP (39). The initial recognition of RNC by SRP is insufficient to reject suboptimal cargos bearing weak signal sequences (40, 41). Instead, a correct cargo strongly stabilizes the otherwise labile early intermediate and thus accelerates formation of the SRP•FtsY closed complex over 10³-fold, whereas suboptimal cargos provide much less stimulation (34, 40, 42). This enables rapid delivery of the correct cargos to the target membrane and provides kinetic discrimination against suboptimal cargos (Fig. S1).TF is a major cotranslational chaperone in bacteria, with an estimated cellular concentration of 50–80 µM (6). With a dissociation constant (K_d) of ∼1 µM for ribosomes (43), TF is bound to virtually every ribosome in the cell. Like SRP, TF contacts the ribosome via the L23 and L29 proteins near the ribosome exit site (3, 5, 44). Also analogous to SRP, TF preferentially interacts with hydrophobic sequences on the nascent polypeptide (1, 2, 4, 45, 46), mediated by a large concave surface rich in hydrophobic residues (1, 3–6). Despite these similarities with SRP, TF directs substrate proteins to distinct biogenesis pathways: It exhibits synthetic lethality with DnaK/J and facilitates the productive folding of cytosolic proteins (1, 4, 7, 9, 11). It also interacts with a subset of secretory and outer membrane proteins and interfaces with the posttranslational SecA/B pathway (8, 10, 12–14).SRP and TF are two distinct biogenesis pathways that a nascent protein must commit to. This raises intriguing questions: How do these two factors, which have overlapping substrate preferences, compete and/or collaborate at the ribosome exit site? How are nascent proteins sorted between them and committed to the correct pathway in a timely and accurate manner? Extensive past work to address these questions has led to different (and sometimes contradictory) models, including (i) TF and SRP compete for binding to the RNC (10, 15, 16, 18); (ii) TF and SRP can bind to the same RNC simultaneously (17, 19–21); (iii) FtsY rejects TF from SRP-bound ribosomes (17); and (iv) TF preferentially occupies longer nascent chains (13, 45–47) and, by inference, SRP preferentially binds short nascent chains. A unifying model that reconciles all these observations and explains how nascent chains on the ribosome are selected by TF or SRP is still lacking. Most importantly, most of the previous studies have focused on the initial binding of SRP or TF to the nascent polypeptide, which may not be the step at which nascent proteins are committed to their respective biogenesis pathways.In this work, we used high-resolution biochemical and biophysical analyses to investigate the interplay between TF and SRP at the ribosome exit site in molecular detail. We show that TF regulates SRP function by three distinct mechanisms, which together enhance the ability of the SRP pathway to reject suboptimal substrates. Our results establish a comprehensive and cohesive model that explains previous observations, delineates the complex interplay between protein biogenesis factors at the ribosome exit site, and provides a conceptual foundation to understand how timely and accurate selection of substrates is achieved in this crowded environment.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Lagging adaptation to warming climate in Arabidopsis thaliana

If climate change outpaces the rate of adaptive evolution within a site, populations previously well adapted to local conditions may decline or disappear, and banked seeds from those populations will be unsuitable for restoring them. However, if such adaptational lag has occurred, immigrants from historically warmer climates will outperform natives and may provide genetic potential for evolutionary rescue. We tested for lagging adaptation to warming climate using banked seeds of the annual weed Arabidopsis thaliana in common garden experiments in four sites across the species’ native European range: Valencia, Spain; Norwich, United Kingdom; Halle, Germany; and Oulu, Finland. Genotypes originating from geographic regions near the planting site had high relative fitness in each site, direct evidence for broad-scale geographic adaptation in this model species. However, genotypes originating in sites historically warmer than the planting site had higher average relative fitness than local genotypes in every site, especially at the northern range limit in Finland. This result suggests that local adaptive optima have shifted rapidly with recent warming across the species’ native range. Climatic optima also differed among seasonal germination cohorts within the Norwich site, suggesting that populations occurring where summer germination is common may have greater evolutionary potential to persist under future warming. If adaptational lag has occurred over just a few decades in banked seeds of an annual species, it may be an important consideration for managing longer-lived species, as well as for attempts to conserve threatened populations through ex situ preservation.Rapid climate change has already caused species range shifts and local extinctions (1) and is predicted to have greater future impacts (2). As the suitable climate space for a species shifts poleward (3), populations previously well adapted to the historical climate in a particular region may experience strong selection to adapt to rapidly warming local temperatures (4–10). Rapid evolutionary response to climate change has already been observed (11, 12), but it remains unclear whether evolutionary response can keep pace with rapidly changing local adaptive optima (6, 8, 13–15). If local adaptation is slower than the rate of climate change, the average fitness of local populations may decline over time (7, 14, 16, 17), possibly resulting in local extinctions and range collapse at the warmer margin. Where such lag exists, we expect that local seeds banked for conservation may no longer be well adapted to their sites of origin (18). However, such adaptational lag may be mitigated by migration or gene flow from populations in historically warmer sites if those populations are better adapted to current conditions in a site than local populations (8, 13, 19, 20). Although adaptational lag has been predicted (4–6, 8, 14, 15, 19, 21, 22), the distinctive signature of mismatch between local population performance and current climate optima has not yet been explicitly demonstrated in nature.Despite evidence for local adaptation in many organisms (23), there have been few explicit tests for the role of specific climate factors in shaping local fitness optima (4, 9, 13). Such tests require growing many genotypes from populations spanning a range of climates in common gardens across a species’ range to decouple climate of origin from geographic variation in other selective factors (4, 6, 14). If adaptation to local climate has occurred, then genotypes from climates similar to each planting site are expected to have high fitness in that site relative to genotypes from dissimilar climates (6). However, if local adaptive optima have shifted with rapid warming trends over the last 50 y, we expect that banked genotypes from historically warmer climates will have higher fitness within a site than banked genotypes of local origin (6, 21, 22).We tested for lagging adaptation to climate using Arabidopsis thaliana, a naturally inbreeding annual species that inhabits a broad climate space across its native Eurasian range (24). A. thaliana exhibits strong circumstantial evidence of climate adaptation, including geographic clines in ecologically important life-history traits (25–28) and in candidate genes associated with these traits (29, 30), as well as genome-wide associations of single nucleotide polymorphisms with climatic factors (31–34). To test explicitly for local adaptation to climate we measured the lifetime fitness of more than 230 accessions from banked seeds originating from a broad range of climates in replicated field experiments in four sites across the species’ native climate range (Fig. 1). We observed that genotypes originating in historically warmer climates outperformed local genotypes, particularly at the northern range limit.Open in a separate windowFig. 1.Map of common garden sites and sites of origin of the 241 native A. thaliana accessions represented in our experiments.     

Thermodynamic origins of protein folding,allostery, and capsid formation in the human hepatitis B virus core protein

HBc, the capsid-forming “core protein” of human hepatitis B virus (HBV), is a multidomain, α-helical homodimer that aggressively forms human HBV capsids. Structural plasticity has been proposed to be important to the myriad functions HBc mediates during viral replication. Here, we report detailed thermodynamic analyses of the folding of the dimeric HBc protomer under conditions that prevented capsid formation. Central to our success was the use of ion mobility spectrometry–mass spectrometry and microscale thermophoresis, which allowed folding mechanisms to be characterized using just micrograms of protein. HBc folds in a three-state transition with a stable, dimeric, α-helical intermediate. Extensive protein engineering showed thermodynamic linkage between different structural domains. Unusual effects associated with mutating some residues suggest structural strain, arising from frustrated contacts, is present in the native dimer. We found evidence of structural gatekeepers that, when mutated, alleviated native strain and prevented (or significantly attenuated) capsid formation by tuning the population of alternative native conformations. This strain is likely an evolved feature that helps HBc access the different structures associated with its diverse essential functions. The subtle balance between native and strained contacts may provide the means to tune conformational properties of HBc by molecular interactions or mutations, thereby conferring allosteric regulation of structure and function. The ability to trap HBc conformers thermodynamically by mutation, and thereby ablate HBV capsid formation, provides proof of principle for designing antivirals that elicit similar effects.The “protein-folding problem” describes how a polypeptide sequence contains all the information needed for it to adopt a specific 3D structure spontaneously (1). The chemistry and thermodynamic code that causes proteins to fold also underpins protein–protein interactions, allostery, and supramolecular assembly. An emerging trend has been the study of model proteins free from kinetic traps, aggregation, or metal binding, features that can confound experimental execution and data interpretation (2, 3). Consequently, model proteins are small (typically <130 residues), soluble monomers with few proline or cysteine residues and no prosthetic groups (2, 3).Although model proteins have been instrumental in taking the field to its current zenith, there is a paucity of experimental insights into the conformational dynamics of larger, oligomeric proteins, especially those implicated in diseases (3). Such proteins usually have complex behavior refractory to detailed experimental studies. However, the connection between sequence, structure, dynamics, and allostery makes studies of larger proteins central to understanding biological function and aiding drug design (vide infra) (4). One such protein is HBc, the capsid-forming “core protein” of human hepatitis B virus (HBV), a major pathogen that kills 600,000 people annually (5). Although excellent vaccines exist, there are no effective cures for extant chronic infections (5, 6). In addition to capsid formation, HBc plays many essential roles in HBV replication (7–9), making it an attractive drug target (10–15).WT HBc is a 183-residue polypeptide comprising a structured capsid-forming region (residues 1–149; Fig. 1A) and a basic, nucleic acid-binding domain (residues 150–183) (16–18). The structured N-terminal region (hereafter HBc_1–149) spontaneously self-assembles in vitro and in vivo to form icosahedral capsid-like particles (CLPs) identical to nucleocapsids isolated from patient serum (19, 20). X-ray crystallography and cryo-EM have characterized the structure of HBc_1–149 within the context of CLPs, virions, and hexamers (16, 19–23). HBc homodimers comprise two structural domains (Fig. 1A): Helices α₃ and α₄ from opposing monomers pack together and form a disulfide-linked, four-helix bundle dimerization interface (visible as protrusions on the capsid exterior; Fig. 1B), whereas α₁, α₂, and α₅ pack together and around the base of the four-helix bundle to create the hydrophobic core of “contact” domains (19). Weak interdimer interactions between contact domains stabilize HBV capsids (19, 24) (Fig. 1B).Open in a separate windowFig. 1.HBc_1–149 dimer structure within HBV capsids. (A) Four-helix bundle dimerization interface (black) is flanked by contact domains (orange and red). Helices are numbered, and the N and C termini of one monomer are indicated. The disulfide link between C61 of each monomer is indicated (cyan). (B) Exterior surface of a T = 4 capsid HBc_1–149 (PDB ID code 1QGT) (19). Dimers around the threefold and fivefold axes are indicated in blue/green and purple/orange, respectively. (Inset) Interacting quasiequivalent HBc_1–149 dimers from the fivefold (purple and orange) and threefold (blue and green) axes are shown. Hydrophobic contacts between contact domains stabilize capsids. Residues that perturb capsid formation when mutated are indicated.Multiple studies show clearly that HBc has a very malleable structure, with this structural plasticity argued to be functionally important (22, 23). This hypothesis accords well with antivirals that modulate HBc structure (11–15, 22, 23). Studies of HBV capsid assembly have inferred the existence of assembly-active (HBc^Ass) and assembly-incompetent (HBc^Inc) HBc conformations (12, 13, 21, 24, 25). However, there are few detailed insights on the thermodynamic origins of structure, allostery, and dynamics for the dimeric HBc_1–149 protomer, where structural plasticity must originate. This arises from dimeric HBc_1–149 being very challenging to study in vitro (compared with the model proteins described above) because it is a 298-residue disulfide-linked homodimer (containing 6 cysteine and 24 proline residues) that aggregates aggressively and forms capsids.Here, we report detailed folding and stability studies of dimeric HBc_1–149. These show HBc_1–149 folds in a three-state transition with a populated, dimeric, α-helical intermediate. Of 29 “chemically conservative” mutants used to probe folding energetics (26), many had similar effects on the stability of the intermediate and native ensembles. The distribution of these mutations was consistent with the intermediate being stabilized by a significant native-like structure. However, some mutations destabilized the native state (N) much less than the intermediate state (I) relative to the denatured state (D), or significantly increased the free energy of unfolding (ΔG_D–N) relative to WT HBc_1–149. This suggests HBc_1–149 contains structural strain arising from frustrated contacts (27, 28). We found evidence of HBc_1–149 adopting multiple native conformers, where capsid assembly-competent conformers were less stable than those incapable of, or attenuated in, capsid formation. Frustrated regions likely contain structural gatekeepers that (28), when mutated, subtly tuned the folding energy landscape and altered capsid assembly. The presence of multiple native conformations and frustrated regions may explain the origins of allostery reported for HBc. Frustration is likely an evolved tradeoff that balances the conflicting requirements of HBc folding with allosteric regulation of native structure, capsid formation, and diverse functions of different conformers (29). The ability to trap HBc conformers thermodynamically by mutation and ablate capsid formation provides a proof of principle for designing antivirals that elicit similar effects.     

Residue-level resolution of alphavirus envelope protein interactions in pH-dependent fusion

Alphavirus envelope proteins, organized as trimers of E2–E1 heterodimers on the surface of the pathogenic alphavirus, mediate the low pH-triggered fusion of viral and endosomal membranes in human cells. The lack of specific treatment for alphaviral infections motivates our exploration of potential antiviral approaches by inhibiting one or more fusion steps in the common endocytic viral entry pathway. In this work, we performed constant pH molecular dynamics based on an atomic model of the alphavirus envelope with icosahedral symmetry. We have identified pH-sensitive residues that cause the largest shifts in thermodynamic driving forces under neutral and acidic pH conditions for various fusion steps. A series of conserved interdomain His residues is identified to be responsible for the pH-dependent conformational changes in the fusion process, and ligand binding sites in their vicinity are anticipated to be potential drug targets aimed at inhibiting viral infections.Alphaviruses, mosquito-borne human pathogens causing severe inflammations and fatal fevers, have infected many millions of people in recent outbreaks worldwide since 2005 (1–3). The lack of a vaccine or specific treatment prompts investigations of the fundamental mechanisms of the alphaviral lifecycle to facilitate the development of effective antiviral therapies (4). Alphaviruses have been reported to enter the cell through receptor-mediated endocytosis. Here, alphaviruses are ferried toward the perinuclear space of the host cell inside vesicles towed by molecular motors and delivered to specific locations for productive replication (5–11). Even when direct entry into the cytoplasm is possible (11–15), the endocytic entry pathway facilitates the transportation of viruses across the crowded cytoplasmic space and delays detection by the immune system without leaving empty capsid or envelope as obvious evidence of the viral infection exposed outside the host cell (10, 11). Before the delivery of its viral genome into the cytoplasm of a host cell, the alphavirus must undergo a critical step of low pH-triggered membrane fusion, which is a common mechanism in the endocytic viral entry pathway among many different viruses. Understanding the mechanism of the low pH-triggered alphaviral membrane fusion is essential for the development of therapies against alphavirus as well as other viruses using similar endocytic entry mechanisms.Recent studies of the lifecycle of alphavirus reveal that a precursor, p62, is first synthesized as a chaperon forming a heterodimer with E1, which is essential for viral budding (16); p62 protects the E1 protein in the low-pH environment of the secretory pathway before being cleaved by cellular furin to produce mature E2-E1 and a smaller fragment, E3 (17–21). After the virus buds from the cytoplasmic membrane, E3 is released from the virus particle under neutral pH conditions outside the host cell (13, 22–24).On the surface of a mature alphavirus, 80 (E2–E1)₃ viral spikes, organized in T = 4 icosahedral symmetry on the viral lipid membrane, enclose the viral capsid and genome (25–43). On internalization of the mature virus in the endosome of the host cell in a new round of infection cycle, the increasingly acidified endosomal environment triggers a series of conformational changes in the alphaviral spike (E2–E1)₃ (38), including the dissociation of E2 (42, 44, 45), release of a fusion loop on E1 (46, 47), and trimerization of E1 (48). The fusion loop, roughly residues 83–100 on the cd loop of each E1 protein (13, 49, 50), in the newly formed E1 homotrimer (HT), inserts into the endosomal membrane. Then, the E1 proteins fold back, pulling the viral and endosomal membranes together and thus, promoting membrane fusion (13, 24).Recently solved high-resolution structures of the alphavirus envelope proteins E2–E1 fitted into cryo-EM data representing the intact virus under both acidic and neutral pH conditions (43, 51, 52) provide excellent atomic models for studies of the low pH-triggered fusion process. The structure of Chikungunya virus (CHIKV) obtained at pH 8.0 represents the initial mature state (M state) of the (E2–E1)₃ viral spike before the fusion process (51). Under pH 5.6, domain B (DB) of E2, which protects the E1 fusion loop, is observed to be disordered in Sindbis virus (52). The rest of the domains of the (E2–E1)₃ spike show moderate conformational differences with an rmsd = 4.0 Å among C_α atoms compared with the structures obtained at pH 8.0 for CHIKV (43, 51). The structure of the envelope proteins in acidic conditions most likely depicts a fusion intermediate (FI) state (52) before E2 dissociation during the low pH-triggered fusion process. In addition, the crystal structure of the folded-back E1 HT (53) is a good model to describe the postfusion state.Based on these atomic models of the E2 and E1 envelope proteins and our previously developed constant pH molecular dynamics (CPHMD) method (54–58), we simulated the envelope proteins with icosahedral symmetry under various pH conditions covering pH 2.0–9.0. We used pH replica exchange in CPHMD and calculated pK_a values using pH titration fitting, which has been shown as a reliable and accurate approach to capture pK_a values of protein residues in various systems (59–64). Through the CPHMD modeling, we calculated the pK_a of the possible pH-sensitive residues (Asp, Glu, and His) in the M, FI, dissociated E2 (Dis), and HT states. We, therefore, derive the shifts in the thermodynamic stabilities originating from each titrating residue for the steps from the M to the FI state (M→FI) of (E2–E1)₃, from the FI to the Dis state (FI→Dis) of E2 proteins, and from the FI to the HT state (FI→HT) of E1 proteins as shown in Fig. 1D. For these processes, we assume that the virus is in the endosomal environment, and we do not consider possible receptor-induced conformational changes. Our residue-level resolution simulations and analyses allow us to identify the critical functional residues with significant pK_a shifts and changes in thermodynamic stability in the low pH-triggered fusion activation. Our results suggest that the most pH-sensitive residues are highly conserved among different alphaviral species and that these critical residues control the pH threshold of fusion activities, provide guidance to further mutagenesis experiments, and lead to more fundamental understanding of low pH-triggered alphaviral membrane fusion.Open in a separate windowFig. 1.Structure and organization of alphaviral envelope proteins. (A) The alphaviral envelope modeled in our simulations. (B) The alphaviral envelope proteins in an MAU. (C) The heterodimer of E2 (DA–DB–DC) and E1 (DI–DII–DIII). (D) Structures of a viral spike in different conformational states simulated for shifts in pK_a values and thermodynamic stabilities. E1 proteins are shown in blue, cyan, and light blue. E2 proteins are shown in red, magenta, and pink.     

Reconstitution of long and short patch mismatch repair reactions using Saccharomyces cerevisiae proteins

A problem in understanding eukaryotic DNA mismatch repair (MMR) mechanisms is linking insights into MMR mechanisms from genetics and cell-biology studies with those from biochemical studies of MMR proteins and reconstituted MMR reactions. This type of analysis has proven difficult because reconstitution approaches have been most successful for human MMR whereas analysis of MMR in vivo has been most advanced in the yeast Saccharomyces cerevisiae. Here, we describe the reconstitution of MMR reactions using purified S. cerevisiae proteins and mispair-containing DNA substrates. A mixture of MutS homolog 2 (Msh2)–MutS homolog 6, Exonuclease 1, replication protein A, replication factor C-Δ1N, proliferating cell nuclear antigen and DNA polymerase δ was found to repair substrates containing TG, CC, +1 (+T), +2 (+GC), and +4 (+ACGA) mispairs and either a 5′ or 3′ strand interruption with different efficiencies. The Msh2–MutS homolog 3 mispair recognition protein could substitute for the Msh2–Msh6 mispair recognition protein and showed a different specificity of repair of the different mispairs whereas addition of MutL homolog 1–postmeiotic segregation 1 had no affect on MMR. Repair was catalytic, with as many as 11 substrates repaired per molecule of Exo1. Repair of the substrates containing either a 5′ or 3′ strand interruption occurred by mispair binding-dependent 5′ excision and subsequent resynthesis with excision tracts of up to ∼2.9 kb occurring during the repair of the substrate with a 3′ strand interruption. The availability of this reconstituted MMR reaction now makes possible detailed biochemical studies of the wealth of mutations identified that affect S. cerevisiae MMR.DNA mismatch repair (MMR) is a critical DNA repair pathway that is coupled to DNA replication in eukaryotes where it corrects misincorporation errors made during DNA replication (1–9). This pathway prevents mutations and acts to prevent the development of cancer (10, 11). MMR also contributes to gene conversion by repairing mispaired bases that occur during the formation of recombination intermediates (3, 4, 12). Finally, MMR acts to suppress recombination between divergent but homologous DNA sequences, thereby preventing the formation of genome rearrangements that can result from nonallelic homologous recombination (4, 13–15).Our knowledge of the mechanism of eukaryotic MMR comes from several general lines of investigation (3–9). Studies of bacterial MMR have provided a basic mechanistic framework for comparative studies (5). Genetic and cell-biology studies, primarily in Saccharomyces cerevisiae, have identified eukaryotic MMR genes, provided models for how their gene products define MMR pathways, and elucidated some of the details of how MMR pathways interact with replication (1–4). Reconstitution studies, primarily in human systems, have identified some of the catalytic features of eukaryotic MMR (7–9, 16, 17). Biochemical and structural studies of S. cerevisiae and human MMR proteins have provided information about the function of individual MMR proteins (6–9).In eukaryotic MMR, mispairs are bound by MutS homolog 2 (Msh2)–MutS homolog 6 (Msh6) and Msh2–MutS homolog 3 (Msh3), two partially redundant complexes of MutS-related proteins (3, 4, 18, 19). These complexes recruit a MutL-related complex, called MutL homoloh 1 (Mlh1)–postmeiotic segregation 1 (Pms1) in S. cerevisiae and Mlh1–postmeiotic segregation 2 (Pms2) in human and mouse (3, 4, 20–23). The Mlh1–Pms1/Pms2 complex has an endonuclease activity suggested to play a role in the initiation of the excision step of MMR (24, 25). Downstream of mismatch recognition is a mispair excision step that can be catalyzed by Exonuclease 1 (Exo1) (26–28); however, defects in both S. cerevisiae and mouse Exo1 result in only a partial MMR deficiency, suggesting the existence of additional excision mechanisms (26, 27, 29). DNA polymerase δ, the single-strand DNA binding protein replication protein A (RPA), the sliding clamp proliferating cell nuclear antigen (PCNA), and the clamp loader replication factor C (RFC) are also required for MMR at different steps, including activation of Mlh1–Pms1/Pms2, stimulation of Exo1, potentially in Exo1-independent mispair excision, and in the gap-filling resynthesis steps of MMR (3, 16, 17, 24, 27, 30–36). Although much is known about these core MMR proteins, it is not well understood how eukaryotic MMR is coupled to DNA replication (1, 2), how excision is targeted to the newly replicated strand (1, 25, 37–39), or how different MMR mechanisms such as Exo1-dependent and -independent subpathways are selected or how many such subpathways exist (1, 24, 27, 29).S. cerevisiae has provided a number of tools for studying MMR, including forward genetic screens for mutations affecting MMR, including dominant and separation-of-function mutations, the ability to evaluate structure-based mutations in vivo, cell biological tools for visualizing and analyzing MMR proteins in vivo, and overproduction of individual MMR proteins for biochemical analysis. However, linking these tools with biochemical systems that catalyze MMR reactions in vitro for mechanistic studies has not yet been possible. Here, we describe the development of MMR reactions reconstituted using purified proteins for the analysis of MMR mechanisms.     

Interrogating the activities of conformational deformed enzyme by single-molecule fluorescence-magnetic tweezers microscopy

Characterizing the impact of fluctuating enzyme conformation on enzymatic activity is critical in understanding the structure–function relationship and enzymatic reaction dynamics. Different from studying enzyme conformations under a denaturing condition, it is highly informative to manipulate the conformation of an enzyme under an enzymatic reaction condition while monitoring the real-time enzymatic activity changes simultaneously. By perturbing conformation of horseradish peroxidase (HRP) molecules using our home-developed single-molecule total internal reflection magnetic tweezers, we successfully manipulated the enzymatic conformation and probed the enzymatic activity changes of HRP in a catalyzed H₂O_2–amplex red reaction. We also observed a significant tolerance of the enzyme activity to the enzyme conformational perturbation. Our results provide a further understanding of the relation between enzyme behavior and enzymatic conformational fluctuation, enzyme–substrate interactions, enzyme–substrate active complex formation, and protein folding–binding interactions.One of the central focuses in protein study is the structure–function relationship, the impact of different conformations on the properties of protein molecules. It has been widely reported that protein molecules with their tertiary structure perturbed or even partially unfolded may be related to protein malfunction or human diseases, because changing protein conformations typically leads to significant differences in their affinity, selectivity, and reactivity (1–17). In modern enzymology, it has extensively been explored that the enzymatic conformation–dynamics–function relationship, especially the dynamic rather than the static perspectives, plays a critical role in the understanding of enzyme mechanisms at the molecular level (18–21). For example, in an enzymatic reaction, formation of the enzyme–substrate complex often involves significant enzymatic active site conformational changes (22–25).Traditional enzymology focused on studying enzymatic reactions at conditions in which the enzymes are fully folded or in their natural states. For example, the studies of enzymatic stability focused on ensemble level activity of enzymes at different physical conditions or chemical environment without probing corresponding change in conformation of enzyme molecules under the same conditions (11, 12, 18–28). In recent years, a number of technical approaches on single-molecule protein conformational manipulation, such as atomic force microscopy (AFM), magnetic tweezers, and optical tweezers, have been developed (29–34). Furthermore, more research has focused on studying enzymatic activity under denaturing conditions, in which enzymes are denatured or are under nonphysiological enzymatic reaction conditions (8, 13, 35–38).Nevertheless, it remains a challenge to characterize the impact of conformational changes of enzyme molecules on their activity under enzymatic conditions while simultaneously probing the enzymatic reactivity changes. Understanding such impacts provides a profound understanding of the enzymatic activity, enzyme–substrate complex formation dynamics, enzymatic product releasing dynamics, and enzymatic reaction energy landscape (14, 39). For example, it has been theoretically studied that the enzymatic activity can be manipulated by an external mechanical force through perturbing the conformation changes of the enzyme molecules (19, 39, 40).It is significant that a single-molecule enzymatic reactivity study, under conformational perturbation and enzymatic reaction conditions, reveals the dependence of enzymatic reactivity on the conformational changes and stability of the enzyme. Key questions of how the enzymatic conformations impact the enzymatic activity and functions are still not clear. For example, can the substrate–enzyme interaction affinity be affected by perturbing enzyme conformation via mechanical force manipulation? Does a conformation-perturbed or even partially unfolded enzyme molecule still have measurable enzymatic reactivity? If so, how much activity will be left at various degrees of external force perturbation? How much can an enzyme molecule tolerate a conformational change under an enzymatic reaction condition? Here we report our work toward obtaining the answers to these questions.In our previous single-molecule FRET magnetic tweezers study, we demonstrated that when a single protein molecule is stretched by magnetic tweezers, a significant change in the conformation, a deformed protein, can be observed (30). Furthermore, we observed that the enzyme–substrate interaction can induce the change of enzymatic active site conformation fluctuation dynamics and conformational flexibility (30).Here we report our work on manipulating single-molecule enzymatic activity using magnetic tweezers to deform the conformations of single-molecule horseradish peroxidase (HRP) enzymes and simultaneously recording the single-molecule fluorogenic enzymatic turnovers by total internal reflection (TIRF) microscopic imaging (Fig. 1). There are specific advantages of using magnetic tweezers to provide an external mechanical force to manipulate single molecule enzyme, including (i) having a force range less than the hydrogen bonding force to protein rupture force (pN to nN); (ii) having no photo-damage and optical cross-talk to single-molecule spectroscopic measurements of enzymatic activity and enzyme conformational changes; and (iii) being capable of simultaneously applying force on a large number of single molecules under the same experimental conditions (41). Combined with TIRF microscopy as a spectroscopic imaging measurement, our single-molecule TIRF-magnetic tweezers provides us a unique capability and opportunity to interrogate the conformation–function relationship of enzyme molecules under enzymatic reaction conditions to specifically study the impact of deforming protein conformation on protein function at a single-molecule level.Open in a separate windowFig. 1.A conceptual scheme of our experimental system. HRP molecules are tethered at one end to a modified glass coverslip, and the immobilized HRP molecules are tethered at the other end to magnetic beads through biotin-streptavidin linking. The magnetic tip of 1,100-Gauss magnetic field at ∼4 mm above the sample glass surface is applied to 1-μm-diameter paramagnetic beads to generate 1- to 2-pN mechanical pulling force on the beads and to the enzyme molecules (SI Text).     

Decision-related pupil dilation reflects upcoming choice and individual bias

A number of studies have shown that pupil size increases transiently during effortful decisions. These decision-related changes in pupil size are mediated by central neuromodulatory systems, which also influence the internal state of brain regions engaged in decision making. It has been proposed that pupil-linked neuromodulatory systems are activated by the termination of decision processes, and, consequently, that these systems primarily affect the postdecisional brain state. Here, we present pupil results that run contrary to this proposal, suggesting an important intradecisional role. We measured pupil size while subjects formed protracted decisions about the presence or absence (“yes” vs. “no”) of a visual contrast signal embedded in dynamic noise. Linear systems analysis revealed that the pupil was significantly driven by a sustained input throughout the course of the decision formation. This sustained component was larger than the transient component during the final choice (indicated by button press). The overall amplitude of pupil dilation during decision formation was bigger before yes than no choices, irrespective of the physical presence of the target signal. Remarkably, the magnitude of this pupil choice effect (yes > no) reflected the individual criterion: it was strongest in conservative subjects choosing yes against their bias. We conclude that the central neuromodulatory systems controlling pupil size are continuously engaged during decision formation in a way that reveals how the upcoming choice relates to the decision maker’s attitude. Changes in brain state seem to interact with biased decision making in the face of uncertainty.Changes in pupil size at constant luminance have long been used as a marker of central autonomic processes linked to cognition (1–4). Many studies over the past decades reported that the pupil dilates while subjects engage in demanding perceptual, cognitive, or economic decision tasks (1–3, 5–17). This decision-related pupil dilation has commonly been linked to the final choice terminating the decision process (6, 14, 16) and the consolidation of the committed decision (6, 16).Changes in pupil size are also linked to changes in brain state. It has been proposed that the decision-related pupil dilation tracks the activity of certain neuromodulatory systems of the brainstem—in particular, the noradrenergic locus coeruleus (5, 7–9, 18) and, possibly, the cholinergic basal forebrain (19) systems. These neuromodulatory systems also activate briefly (“phasically”) during perceptual decisions, such as visual target detection (5, 20–24), likely mediated via feedback connections from the prefrontal cortex (5, 25). The modulatory neurotransmitters released from the projections of these brainstem systems, in turn, shape the internal state of cortical networks, for instance, by boosting the gain of neural interactions (5, 7, 26). Thus, these brainstem systems might also shape decision computations in cortical networks—provided that they are activated already during decision formation. If so, these systems might affect the decision process, over and above shortening the time to respond. For instance, they might govern the decision maker’s ability to overcome his or her intrinsic bias.Here, we addressed these issues noninvasively in humans by linking decision-related pupil dilation to the time course, outcome, and bias of a protracted perceptual decision process. Many perceptual decisions are not transient events but evolve gradually over several hundreds of milliseconds, due to the slow accumulation of noisy sensory information (27–33). Further, perceptual decisions are, like economic decisions (34), prone to strong biases that are not due to external asymmetries in the magnitude or probability of payoffs for certain choices. In particular “yes” vs. “no” detection decisions depend on the idiosyncratic (liberal or conservative) attitude of the decision maker with respect to saying “yes” or “no” (35, 36).We thus measured pupil size in subjects performing a challenging yes–no visual contrast detection task at constant luminance (Fig. 1A). A general linear model (GLM) (37) allowed us to disentangle different temporal components of the neural input to the sluggish system controlling pupil size. This approach revealed that decision-related pupil dilation was not only driven by subjects’ final choice and the concomitant motor response, but also by a (stronger) sustained component throughout the preceding decision process. Further, the dilation amplitude was bigger for yes than for no choices. This pupil choice effect was due to the conservative subjects who decided yes against their bias. Taken together, our findings point to an intricate interplay between changes in internal brain state and biased decision making in the face of uncertainty.Open in a separate windowFig. 1.Task and behavioral results. (A) Sequence of events during a single trial. Dynamic noise is continuously present in a circular aperture around fixation. During the decision interval (onset cued by a tone), the subject searches for a faint grating signal superimposed onto the noise and indicates the yes or no choice by button press. The signal is shown at high contrast for illustration purposes only. In the actual experiment, its contrast was titrated to each individual’s detection threshold. (B) Stimulus types during the decision interval and possible choices of the subject, yielding the four trial categories of signal-detection theory. (C) Distribution of trial types, pooled across all subjects. (D) Reaction-time distributions for each trial type, pooled across all subjects. (E) Normalized reaction times, sorted by trial type and averaged across the group. RT, reaction time. Error bars, SEM.     

From the Cover: Synchronizing theta oscillations with direct-current stimulation strengthens adaptive control in the human brain

Executive control and flexible adjustment of behavior following errors are essential to adaptive functioning. Loss of adaptive control may be a biomarker of a wide range of neuropsychiatric disorders, particularly in the schizophrenia spectrum. Here, we provide support for the view that oscillatory activity in the frontal cortex underlies adaptive adjustments in cognitive processing following errors. Compared with healthy subjects, patients with schizophrenia exhibited low frequency oscillations with abnormal temporal structure and an absence of synchrony over medial-frontal and lateral-prefrontal cortex following errors. To demonstrate that these abnormal oscillations were the origin of the impaired adaptive control in patients with schizophrenia, we applied noninvasive dc electrical stimulation over the medial-frontal cortex. This noninvasive stimulation descrambled the phase of the low-frequency neural oscillations that synchronize activity across cortical regions. Following stimulation, the behavioral index of adaptive control was improved such that patients were indistinguishable from healthy control subjects. These results provide unique causal evidence for theories of executive control and cortical dysconnectivity in schizophrenia.Networks involving frontal cortex allow us to adapt our actions to dynamic environments and adjust information processing following errors (1). This adaptive control is a hallmark of healthy goal-directed behavior, but it is dysfunctional in a variety of psychiatric and neurological disorders (2–4). In particular, the adaptive-control deficits that are a central feature of schizophrenia are highly predictive of poor functioning in daily life (5). In the laboratory, a canonical signature of adaptive control is the magnitude of posterror slowing of reaction time (RT), in which healthy subjects respond more slowly after making an error (6, 7). Patients with schizophrenia show an impaired ability to slow down their responses after errors (4, 8–13, but also 14, 15), providing a laboratory index that captures the rigid, perseverative, and maladaptive behavior that is characteristic of the disorder (8, 16).Adaptive control in the healthy brain is hypothesized to depend partly on the low-frequency EEG oscillations measured over medial-frontal cortex. The low-frequency oscillations are thought to reflect coordinated activity across the diverse set of brain areas recruited to perform a task (1, 17–22). In addition, medial-frontal theta (4–8 Hz) oscillations appear to signal the need for adaptive control across a variety of tasks and situations. Situations that call for adaptive control include stimulus novelty, response conflict, negative feedback, and behavioral errors, with all of these situations sharing a common medial-frontal spectral signature in the theta band (21). However, the functional significance of medial-frontal theta may be much broader than simply functioning as an alarm for the adaptive-control system. Theta oscillations have been hypothesized to serve as the temporal code that coordinates neuronal populations involved in implementing control (1, 19–21), with medial-frontal cortex working in concert with dorsolateral prefrontal areas to support flexible, adaptive behavior (1, 23–26). For example, when an error occurs, network-level oscillations allow executive mechanisms to adjust subordinate cognitive mechanisms (e.g., perceptual attention, response-selection thresholds). In the present study, we examined whether the executive-control deficits in patients with schizophrenia arise from communication and coordination failures among the cognitive subsystems flexibly linked through low-frequency oscillatory activity (3, 27, 28).We recorded EEG oscillations from outpatients with schizophrenia and demographically matched healthy controls (Table S1) while they performed a two-alternative forced-choice target discrimination task with response deadlines and interleaved stop-signal trials sufficient to produce errors (similar to a go/no-go task) (Fig. 1A). We reasoned that if temporal structured medial-frontal theta activity underlies normal adaptive control, the patients should exhibit abnormal medial-frontal theta provided that they show abnormal posterror slowing.Open in a separate windowFig. 1.tDCS model, task, and the behavioral and spectral signatures of adaptive control. (A) Target discrimination task requiring subjects to report the color of the target (red vs. blue, magenta vs. green, or purple vs. yellow) by pressing one of two buttons on a handheld gamepad. (B) Mean posterror RT slowing and mean intertrial phase coherence shown across stimulation conditions and subject groups. HC, healthy controls; SZ, patients with schizophrenia. (C) Mean total power and mean evoked power as in B. (D) Intertrial phase coherence (Left), total power (Middle), and evoked power (Right) at Cz on error minus correct trials shown across subject groups in the sham condition. Topographies show spatial distribution from the selected time-frequency measurement windows (green rectangles). (Far Left) Source estimate of intertrial phase coherence centered on Cz peak activity for healthy subjects in the sham condition is shown across sagittal, coronal, and axial MRI slices. A, anterior; L, left; P, posterior; R, right. (E) Schematic of tDCS montage and the modeled distribution of current during active tDCS on top and front views of a 3D reconstruction of the cortical surface. (F) Response-related time-frequency representations and topographies as in D shown across subject groups in the anodal tDCS condition. The analytical window for intertrial phase coherence and total power analyses was 4–8 Hz, −50 to 300 ms periresponse. The analytical window for evoked power analyses was 4–8 Hz, 0–100 ms postresponse. Data were scalp Laplacian-transformed.