Cytonuclear interactions affect adaptive traits of the annual plant Arabidopsis thaliana in the field

Although the contribution of cytonuclear interactions to plant fitness variation is relatively well documented at the interspecific level, the prevalence of cytonuclear interactions at the intraspecific level remains poorly investigated. In this study, we set up a field experiment to explore the range of effects that cytonuclear interactions have on fitness-related traits in Arabidopsis thaliana. To do so, we created a unique series of 56 cytolines resulting from cytoplasmic substitutions among eight natural accessions reflecting within-species genetic diversity. An assessment of these cytolines and their parental lines scored for 28 adaptive whole-organism phenotypes showed that a large proportion of phenotypic traits (23 of 28) were affected by cytonuclear interactions. The effects of these interactions varied from slight but frequent across cytolines to strong in some specific parental pairs. Two parental pairs accounted for half of the significant pairwise interactions. In one parental pair, Ct-1/Sha, we observed symmetrical phenotypic responses between the two nuclear backgrounds when combined with specific cytoplasms, suggesting nuclear differentiation at loci involved in cytonuclear epistasis. In contrast, asymmetrical phenotypic responses were observed in another parental pair, Cvi-0/Sha. In the Cvi-0 nuclear background, fecundity and phenology-related traits were strongly affected by the Sha cytoplasm, leading to a modified reproductive strategy without penalizing total seed production. These results indicate that natural variation in cytoplasmic and nuclear genomes interact to shape integrative traits that contribute to adaptation, thereby suggesting that cytonuclear interactions can play a major role in the evolutionary dynamics of A. thaliana.The genomes of eukaryotes originate from ancient endosymbiotic associations that eventually led to energy-harnessing organelles: mitochondria, common to all eukaryotes, and chloroplasts in the “green” lineage. The evolution of endosymbionts into cellular organelles was accompanied by massive gene loss, with a large proportion being transferred to the nucleus (1, 2). Nevertheless, mitochondria and chloroplasts retained a few (30–80) protein-encoding genes that play crucial roles in energy metabolism (respiration and photosynthesis). Mitochondrion and chloroplast metabolisms rely on the proper interaction of nuclear-encoded proteins and their counterparts encoded in the organelle genome. Consequently, the genes in nuclear and organellar compartments are expected to be coadapted (3).Cytonuclear coadaptation has been demonstrated by altered phenotypes observed on interspecific exchanges of cytoplasm between related species in mammals (4), yeast (5), arthropods (6), and plants, whose interspecific crosses are frequently successful (7). These alterations affect organelle function and even the organism phenotype, indicating epistasis between nuclear and cytoplasmic genes. Although cytonuclear coadaptation is generally studied at the interspecific level, the existence of intraspecific genetic diversity in organelle genomes suggests a potential for genomic coadaptation within species. A few studies have reported phenotypic effects of intraspecific cytonuclear epistasis in nonplant species (8–11). In plants, many studies have focused on cytoplasmic male sterility (CMS), an impairment of pollen production governed by nucleo-mitochondrial interactions in some hermaphroditic species (12), in particular in crops and their relatives (13). The phenotypic effects of intraspecific cytonuclear epistasis other than CMS have been reported in only a limited number of plant systems (14–17), with evidence that cytoplasmic variation contributes to local adaptation (18, 19).In recent years, several studies using reciprocal segregating populations of the model plant Arabidopsis thaliana have investigated the effect of cytonuclear epistasis on a number of laboratory-measured phenotypes such as the metabolome, defense chemistry and growth (17, 20, 21), water-use efficiency (22, 23), and seed germination (24, 25). Although some studies have reported significant effects of cytonuclear epistasis (17, 20, 21, 23, 25), others have found additive cytoplasmic effects but with weak or no cytonuclear epistasis (22). Each of these studies (with the exception of ref. 25) was, however, based on a single reciprocal cross between two natural accessions, thereby preventing the estimation of the prevalence of cytonuclear epistasis in this species. In addition, although these reports involve adaptive traits (26–30), the investigation of the effect of cytonuclear epistasis on adaptive phenotypes in field conditions is, at best, scarce in A. thaliana.Here, following the modern standards of ecological genomics (31), we explored the prevalence of cytonuclear interactions on adaptive whole-organism traits in the model plant A. thaliana in a field experiment. To do so, based on eight natural accessions of a core collection that covers a significant part of the species’ cytoplasmic and nuclear genetic diversity in A. thaliana (25, 32), we created eight series of seven cytolines. Cytolines are genotypes that combine the nuclear genome from one parent with the organelle genomes of another (33). We examined the cytolines and their parental accessions for effects of cytonuclear interactions on 28 field-measured traits related to germination, phenology, resource acquisition, plant architecture and seed dispersal, fecundity, and survival.     

Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains.Mutations can interact with one another and with their broader genetic background to affect fitness, a phenomenon known as epistasis (1). Epistasis plays a key role in many aspects of biology, including theories of speciation (2, 3), the evolution and maintenance of sex (4, 5), adaptation (6–8), and evolutionary contingency (9, 10). Whereas early experimental studies focused on interactions between deletion or other knockout mutations, advances in genomic technologies now allow direct tests of interactions between spontaneously occurring beneficial mutations (11–16). Studies that manipulate beneficial mutations have the potential to identify general patterns that may underlie some degree of predictability in adaptive evolutionary outcomes. For example, interactions between beneficial mutations often follow a pattern of diminishing returns epistasis, such that the marginal benefit of additional mutations declines with the fitness of the recipient genotype (11–16). Diminishing returns epistasis reflects a global interaction between mutations that interact at the level of fitness (16). This pattern is consistent with the frequent observation of decelerating fitness trajectories as populations adapt to constant environments and the observation of a negative relationship between the starting fitness of a population and its initial rate of fitness increase (17–19). In apparent contrast, some theoretical work predicts an excess of positive interactions along adaptive trajectories, highlighting the need for continued research in this area (20–22).Most studies that have examined interactions that affect beneficial mutations have focused on interactions between mutations arising in a single population or in replicate populations evolved from a common ancestor (11, 12, 14, 23, 24). In these cases, there are relatively few mutational differences separating different genotypes, limiting our ability to extrapolate findings to an understanding of the influence of mutation interactions on adaptive evolution in genetically diverse natural populations. Indeed, introgression experiments indicate the importance of the broader genetic background in determining the effect of specific genetic regions (reviewed in ref. 25), and even the interaction between two focal mutations depends strongly and perhaps unpredictably on the genetic background in which they are measured (15).A better understanding of the interaction between beneficial mutations and diverse genetic backgrounds will allow us to address whether mutations selected in one background will tend to have similar effects across different backgrounds. This question is particularly important in considering the evolution of bacterial populations in which the horizontal transfer and integration of short homologous DNA sequences—typically on the order of ∼50–500 bp in Escherichia coli (26, 27)—means that the fate of new beneficial mutations will depend strongly on their interaction with the background of recipient strains. If the influence of interactions tends to be small, the effect of a beneficial mutation will be mostly independent of its genetic background, and it can spread broadly. If interactions are common, they may prevent the spread of potentially beneficial mutations between lineages. This kind of barrier has been proposed as a component of a bacterial species concept (28).To the extent that mutation effects differ across genetic backgrounds, it is of interest to identify attributes of those backgrounds that might explain those differences. At least three candidate mechanisms have been presented: (i) The potential for differences in the specific genetic interactions that influence the effect of a new mutation increases with genetic distance. For this reason, closely related strains are expected, on average, to respond more similarly to the same new mutation than are divergent strains (2). (ii) Genetically divergent lineages can convergently evolve similar underlying genetic architectures through, for example, selection in similar ecological niches (29). For example, a comparison of bacterial metabolic networks revealed a correlation between metabolic network architecture and ecological profile that is not explained by phylogenetic relatedness (30, 31). To the extent that genetic architecture influences the effect of mutations, organisms that have similar architectures may respond similarly to an introduced mutation even if they are not genetically closely related. (iii) The relative benefit of a mutation transferred into different lineages is determined by the initial fitness of that lineage. This possibility stems from the frequent finding of globally determined fitness-dependent negative interactions between beneficial mutations (11, 32, 33). Finally, interactions between mutations and the broader genetic background may be essentially unpredictable, perhaps depending on relatively small numbers of large effect interactions.To examine these possibilities, we transferred four beneficial mutations that fixed in a long-term laboratory-evolved E. coli population to a diverse set of E. coli natural isolate strains (12). By measuring the fitness effect of many mutation–strain combinations, we determined the effect of interactions between the focal mutations and recipient genetic backgrounds. We also examined whether the fitness effects of the beneficial mutations were correlated with phylogenetic relatedness and/or similarity of diet niche profile—which we use as a proxy for ecological similarity—between the original and recipient genetic backgrounds. We found that the fitness of all mutations depended strongly on genetic background. This effect was not explained by differences in the genetic relatedness of the recipients and was only weakly correlated with their ecological similarity. In contrast, there was a significant relationship between mutational effects and the initial fitness of the recipient strains. This relationship followed a pattern of diminishing returns whereby more fit strains benefited less from addition of the mutations.     

Predictive Value of Brain Natriuretic Peptides in Patients on Peritoneal Dialysis: Results from the ADEMEX Trial

Background and objectives: Natriuretic peptides have been suggested to be of value in risk stratification in dialysis patients. Data in patients on peritoneal dialysis remain limited.Design, setting, participants, & measurements: Patients of the ADEMEX trial (ADEquacy of peritoneal dialysis in MEXico) were randomized to a control group [standard 4 × 2L continuous ambulatory peritoneal dialysis (CAPD); n = 484] and an intervention group (CAPD with a target creatinine clearance ≥60L/wk/1.73 m²; n = 481). Natriuretic peptides were measured at baseline and correlated with other parameters as well as evaluated for effects on patient outcomes.Results: Control group and intervention group were comparable at baseline with respect to all measured parameters. Baseline values of natriuretic peptides were elevated and correlated significantly with levels of residual renal function but not with body size or diabetes. Baseline values of N-terminal fragment of B-type natriuretic peptide (NT-proBNP) but not proANP(1–30), proANP(31–67), or proANP(1–98) were independently highly predictive of overall survival and cardiovascular mortality. Volume removal was also significantly correlated with patient survival.Conclusions. NT-proBNP have a significant predictive value for survival of CAPD patients and may be of value in guiding risk stratification and potentially targeted therapeutic interventions.Plasma levels of cardiac natriuretic peptides are elevated in patients with chronic kidney disease, owing to impairment of renal function, hypertension, hypervolemia, and/or concomitant heart disease (1–7). Atrial natriuretic peptide (ANP) and particularly brain natriuretic peptide (BNP) levels are linked independently to left ventricular mass (3–5,8–16) and function (3,6–17) and predict total and cardiovascular mortality (1,3,8,10,12,18) as well as cardiac events (12,19). ANP and BNP decrease significantly during hemodialysis treatment but increase again during the interdialytic interval (1,2,4,6,7,14,17,20–23). Levels in patients on peritoneal dialysis (PD) have been found to be lower than in patients on hemodialysis (11,24–26), but the correlations with left ventricular function and structure are maintained in both types of dialysis modalities (11,15,27,28).The high mortality of patients on peritoneal dialysis and the failure of dialytic interventions to alter this mortality (29,30) necessitate renewed attention into novel methods of stratification and identification of patients at highest risk to be targeted for specific interventions. Cardiac natriuretic peptides are increasingly considered to fulfill this role in nonrenal patients. Evaluations of cardiac natriuretic peptides in patients on PD have been limited by small numbers (3,9,11,12,15,24–26) and only one study examined correlations between natriuretic peptide levels and outcomes (12). The PD population enrolled in the ADEMEX trial offered us the opportunity to evaluate cardiac natriuretic peptides and their value in predicting outcomes in the largest clinical trial ever performed on PD (29,30). It is hoped that such an evaluation would identify patients at risk even in the absence of overt clinical disease and hence facilitate or encourage interventions with salutary outcomes.     

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.     

Structural interactions of a voltage sensor toxin with lipid membranes

Protein toxins from tarantula venom alter the activity of diverse ion channel proteins, including voltage, stretch, and ligand-activated cation channels. Although tarantula toxins have been shown to partition into membranes, and the membrane is thought to play an important role in their activity, the structural interactions between these toxins and lipid membranes are poorly understood. Here, we use solid-state NMR and neutron diffraction to investigate the interactions between a voltage sensor toxin (VSTx1) and lipid membranes, with the goal of localizing the toxin in the membrane and determining its influence on membrane structure. Our results demonstrate that VSTx1 localizes to the headgroup region of lipid membranes and produces a thinning of the bilayer. The toxin orients such that many basic residues are in the aqueous phase, all three Trp residues adopt interfacial positions, and several hydrophobic residues are within the membrane interior. One remarkable feature of this preferred orientation is that the surface of the toxin that mediates binding to voltage sensors is ideally positioned within the lipid bilayer to favor complex formation between the toxin and the voltage sensor.Protein toxins from venomous organisms have been invaluable tools for studying the ion channel proteins they target. For example, in the case of voltage-activated potassium (Kv) channels, pore-blocking scorpion toxins were used to identify the pore-forming region of the channel (1, 2), and gating modifier tarantula toxins that bind to S1–S4 voltage-sensing domains have helped to identify structural motifs that move at the protein–lipid interface (3–5). In many instances, these toxin–channel interactions are highly specific, allowing them to be used in target validation and drug development (6–8).Tarantula toxins are a particularly interesting class of protein toxins that have been found to target all three families of voltage-activated cation channels (3, 9–12), stretch-activated cation channels (13–15), as well as ligand-gated ion channels as diverse as acid-sensing ion channels (ASIC) (16–21) and transient receptor potential (TRP) channels (22, 23). The tarantula toxins targeting these ion channels belong to the inhibitor cystine knot (ICK) family of venom toxins that are stabilized by three disulfide bonds at the core of the molecule (16, 17, 24–31). Although conventional tarantula toxins vary in length from 30 to 40 aa and contain one ICK motif, the recently discovered double-knot toxin (DkTx) that specifically targets TRPV1 channels contains two separable lobes, each containing its own ICK motif (22, 23).One unifying feature of all tarantula toxins studied thus far is that they act on ion channels by modifying the gating properties of the channel. The best studied of these are the tarantula toxins targeting voltage-activated cation channels, where the toxins bind to the S3b–S4 voltage sensor paddle motif (5, 32–36), a helix-turn-helix motif within S1–S4 voltage-sensing domains that moves in response to changes in membrane voltage (37–41). Toxins binding to S3b–S4 motifs can influence voltage sensor activation, opening and closing of the pore, or the process of inactivation (4, 5, 36, 42–46). The tarantula toxin PcTx1 can promote opening of ASIC channels at neutral pH (16, 18), and DkTx opens TRPV1 in the absence of other stimuli (22, 23), suggesting that these toxin stabilize open states of their target channels.For many of these tarantula toxins, the lipid membrane plays a key role in the mechanism of inhibition. Strong membrane partitioning has been demonstrated for a range of toxins targeting S1–S4 domains in voltage-activated channels (27, 44, 47–50), and for GsMTx4 (14, 50), a tarantula toxin that inhibits opening of stretch-activated cation channels in astrocytes, as well as the cloned stretch-activated Piezo1 channel (13, 15). In experiments on stretch-activated channels, both the d- and l-enantiomers of GsMTx4 are active (14, 50), implying that the toxin may not bind directly to the channel. In addition, both forms of the toxin alter the conductance and lifetimes of gramicidin channels (14), suggesting that the toxin inhibits stretch-activated channels by perturbing the interface between the membrane and the channel. In the case of Kv channels, the S1–S4 domains are embedded in the lipid bilayer and interact intimately with lipids (48, 51, 52) and modification in the lipid composition can dramatically alter gating of the channel (48, 53–56). In one study on the gating of the Kv2.1/Kv1.2 paddle chimera (53), the tarantula toxin VSTx1 was proposed to inhibit Kv channels by modifying the forces acting between the channel and the membrane. Although these studies implicate a key role for the membrane in the activity of Kv and stretch-activated channels, and for the action of tarantula toxins, the influence of the toxin on membrane structure and dynamics have not been directly examined. The goal of the present study was to localize a tarantula toxin in membranes using structural approaches and to investigate the influence of the toxin on the structure of the lipid bilayer.     

Inferring fitness landscapes by regression produces biased estimates of epistasis

The genotype–fitness map plays a fundamental role in shaping the dynamics of evolution. However, it is difficult to directly measure a fitness landscape in practice, because the number of possible genotypes is astronomical. One approach is to sample as many genotypes as possible, measure their fitnesses, and fit a statistical model of the landscape that includes additive and pairwise interactive effects between loci. Here, we elucidate the pitfalls of using such regressions by studying artificial but mathematically convenient fitness landscapes. We identify two sources of bias inherent in these regression procedures, each of which tends to underestimate high fitnesses and overestimate low fitnesses. We characterize these biases for random sampling of genotypes as well as samples drawn from a population under selection in the Wright–Fisher model of evolutionary dynamics. We show that common measures of epistasis, such as the number of monotonically increasing paths between ancestral and derived genotypes, the prevalence of sign epistasis, and the number of local fitness maxima, are distorted in the inferred landscape. As a result, the inferred landscape will provide systematically biased predictions for the dynamics of adaptation. We identify the same biases in a computational RNA-folding landscape as well as regulatory sequence binding data treated with the same fitting procedure. Finally, we present a method to ameliorate these biases in some cases.An organism’s fitness or expected reproductive output is determined by its genotype, environment, and, possibly, the frequencies of other genotypes in the population. In the simplified setting of a fixed environment without frequency-dependent effects, as in many experimental populations (1–5), fitnesses are described by a map from genotypes to reproductive rates called the fitness landscape.The dynamics of an adapting population fundamentally depend on characteristics of the organism’s fitness landscape (6–24). However, mapping out an organism’s fitness landscape is virtually impossible in practice because of the coarse resolution of fitness measurements and because of epistasis: the fitness contribution of one locus may depend on the states of other loci. To account for all possible forms of epistasis, a fitness landscape must assign a potentially different fitness to each genotype, and the number of genotypes increases exponentially with the number of loci.As a result of these practical difficulties, fitness landscapes have been directly measured in only very limited cases, such as for individual proteins, RNA molecules, or viruses. Even in these limited cases, genetic variation was restricted to a handful of genetic sites (25–41). Alternatively, one might try to infer properties of a fitness landscape from a time series of samples from a reproducing population. Despite considerable effort along these lines (19, 42–44), this approach is difficult, and such inferences from time series can be subject to systematic biases (45). As a result, very little is known about fitness landscapes in nature, despite their overwhelming importance in shaping the course of evolution.Technological developments now allow researchers to assay growth rates of microbes or enzymatic activities of individual proteins and RNAs for millions of variants (46–48). As a result, researchers are now beginning to sample and measure larger portions of the fitness landscapes than previously possible. Nonetheless, even in these cases, the set of sampled genotypes still represents a tiny proportion of all genotypes and also, likely, a tiny proportion of all viable genotypes.To draw conclusions from the limited number of genotypes whose fitnesses that can be assayed, researchers fit statistical models, notably by penalized regression, that approximate the fitness landscape based on the data available. This situation is perhaps best illustrated by recent studies of fitness for the HIV-1 virus based on the measured reproductive capacity of HIV-derived amplicons inserted into a resistance test vector (49, 50). These HIV genotypes were sampled from infected patients. [An alternative approach, often used for measuring activities of an individual enzyme, is to introduce mutations randomly into a WT sequence (47, 51–54).] Whereas the entire fitness landscape of HIV-1 consists of reproductive values for roughly 2^1,800 ≈ 10⁶⁰⁰ genotypes, only ≈ 70,000 genotypes were assayed in the experiment (49). Researchers therefore approximated the fitness landscape by penalized regression, based on the measured data, using an expansion in terms of main effects of loci and epistatic interactions between loci. The principle goal of estimating the underlying fitness landscape was to assess the extent and form of epistasis (49) and more generally, understand how adaptation would proceed on such a landscape (50).These studies (49, 50) and other high-throughput fitness measurement studies (46–48) produce massive amounts of data, but not nearly enough data to determine an entire fitness landscape. This difficulty presents the field with several pressing questions. Do statistical approximations based on available data faithfully reproduce the relevant aspects of the true fitness landscape and accurately predict the dynamics of adaptation? Or do biases arising from statistical fits or measurement noise influence the conclusions that we draw from such data?Here, we begin to address these fundamental questions about empirical fitness measurements and how they inform our understanding of the underlying fitness landscape and evolution on the landscape. We study the effects of approximating a fitness landscape from data in terms of main and epistatic effects of loci. We show that such approximations, which are required to draw any general conclusions from a limited sample of genotypes, are subject to two distinct sources of biases. Although these biases are known features of linear regressions, they have important consequences for the biological quantities inferred from such fitness landscapes. These biases systematically alter the form of epistasis in the inferred fitness landscape compared with the true underlying landscape. In particular, the inferred fitness landscape will typically exhibit less local ruggedness than the true landscape, and it will suggest that evolutionary trajectories are less predictable than they actually are in the true landscape.Most of our analysis is based on samples from mathematically constructed fitness landscapes. However, we argue that the types of biases that we identify apply generally and in more biologically realistic situations. Indeed, we show that the same types of biases occur in RNA-folding landscapes as well as empirically measured regulatory sequence binding landscapes.Although it may be impossible to completely remove these biases, we conclude by suggesting steps to mitigate the biases in some cases.     

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).     

Highly efficient full-length hepatitis C virus genotype 1 (strain TN) infectious culture system

Chronic infection with hepatitis C virus (HCV) is an important cause of end stage liver disease worldwide. In the United States, most HCV-related disease is associated with genotype 1 infection, which remains difficult to treat. Drug and vaccine development was hampered by inability to culture patient isolates representing HCV genotypes 1–7 and subtypes; only a recombinant 2a genome (strain JFH1) spontaneously replicated in vitro. Recently, we identified three mutations F1464L/A1672S/D2979G (LSG) in the nonstructural (NS) proteins, essential for development of full-length HCV 2a (J6) and 2b (J8) culture systems in Huh7.5 cells. Here, we developed a highly efficient genotype 1a (strain TN) full-length culture system. We initially found that the LSG substitutions conferred viability to an intergenotypic recombinant composed of TN 5′ untranslated region (5′UTR)-NS5A and JFH1 NS5B-3′UTR; recovered viruses acquired two adaptive mutations located in NS3 and NS4B. Introduction of these changes into a replication-deficient TN full-length genome, harboring LSG, permitted efficient HCV production. Additional identified NS4B and NS5B mutations fully adapted the TN full-length virus. Thus, a TN genome with 8 changes (designated TN cell-culture derived, TNcc) replicated efficiently and released infectious particles of ∼5 log₁₀ focus-forming units per mL; passaged TNcc did not require additional changes. IFN-α and directly acting antivirals targeting the HCV protease, NS5A, and NS5B, each inhibited full-length TN infection dose-dependently. Given the unique importance of genotype 1 for pathogenesis, this infectious 1a culture system represents an important advance in HCV research. The approach used and the mutations identified might permit culture development for other HCV isolates, thus facilitating vaccine development and personalized treatment.Hepatitis C virus (HCV) chronically infects an estimated 130–170 million people worldwide. The infection increases the risk of developing liver cirrhosis and liver cancer and results in more than 350,000 deaths annually. No HCV vaccine is available. Current standard treatment is based on IFN-α/ribavirin, which, however, has low efficacy against the most prevalent HCV variants (1). Incorporation of directly acting antivirals (DAAs) in treatment regimens improves sustained viral response rate, but a favorable outcome is challenged by fast emergence of drug resistance and differential responses of the different HCV genotypes (2). Thus, HCV infection continues to be a huge health and economic burden to the world population, and improved in vitro experimental systems would be important to permit additional studies of new antivirals and associated resistance patterns.HCV is a small enveloped virus belonging to the genus Hepacivirus in the family Flaviviridae. The HCV genome is a positive-sense single-strand RNA (∼9.6 kb), consisting of a single ORF flanked by 5′ and 3′ untranslated regions (UTRs). The ORF encodes virus structural proteins (core, E1, and E2), p7, and six nonstructural (NS) proteins NS2, NS3, NS4A, NS4B, NS5A, and NS5B (1). HCV isolates are classified into seven major variants (genotypes 1–7) and numerous subtypes (a, b, etc.) differing by ∼30% and ∼20%, respectively, in nucleotide and amino acid sequences (3). Genotype 1 is the most prevalent in the world. In the United States, Japan, China, and southern Europe over 70% of HCV patients are infected with genotype 1 (4–7). In northern Europe, genotype 1 accounts for ∼50% of HCV infections (8). Genotype 1 infection is more resistant to IFN-based treatment than infection with other genotypes (1).In vitro HCV culture systems are needed to study treatment regimens and associated viral resistance. However, drug and vaccine development have been greatly hampered by inability to culture patient isolates in vitro. Although a number of HCV full-length clones were shown to be infectious in chimpanzees (ref. 9 and cited references therein), only JFH1 (genotype 2a) spontaneously replicated in human hepatoma cells (Huh7 and its derivatives) and released infectious virus particles (10, 11). Efficient growth of JFH1 required culture adaptive mutations (12). Recently, we reported efficient J6cc (2a) and J8cc (2b) full-length culture systems (13); subsequently Date et al. reported on a full-length system for 2a strain JFH2 (14). A single full-length genotype 1a genome, H77-S, carrying mutations identified in the subgenomic replicon of the same strain, has been reported to release relatively small amounts of virus particles (15). The Con1 (1b) full-length culture system was reported, but a very low level of replication has limited its utility (16). Thus, efficient HCV full-length culture systems remained limited to genotype 2 isolates. The clinical importance of the marked genetic differences between HCV genotype isolates poses a critical need for development of robust full-length culture systems for HCV genotype 1 isolates.The unique replication capacity of JFH1 has permitted the development of JFH1-based HCV recombinants (17); we and others have reported different inter- and intragenotypic recombinants including core-NS2 (17–24), 5′UTR-NS2 (25), NS3 protease/NS4A (26, 27), NS5A (28), and core-NS3 protease plus NS4A-NS5A (29) of various genotypes. These JFH1-based culture systems have been used for genotype-specific studies of HCV genes (19, 20, 22, 25–28, 30), for testing of HCV DAAs (26–28) and neutralizing antibodies (19, 20, 22, 30), and for studying aspects of virus–host interaction (25, 31, 32). Through studies of J6 (2a) recombinants with the entire or partial NS5B and 3′UTR from JFH1, we recently identified adaptive mutations F1464L in NS3 and A1672S in NS4A, designated LS (13). Combination of LS with selected mutations in NS5B and the 3′UTR allowed replication of the full-length J6 genome, which led to the identification of an additional unique mutation D2979G in NS5B, designated G (13). The LSG substitutions permitted the development of robust HCV full-length culture systems for J6 and for the prototype genotype 2b J8 strain (13). In this study, we used LSG as a critical component and a unique approach to develop a highly efficient full-length genotype 1a (strain TN) infectious culture system, named TN cell-culture derived (TNcc). The TNcc replicated efficiently in culture, released viral particles of ∼10⁵ focus-forming units (FFU)/mL and did not require additional mutations after viral passage. We demonstrated that full-length TN responded dose dependently to IFN-α, as well as HCV DAAs already used in the clinic and being tested in clinical trials.     

Programmable motion of DNA origami mechanisms

DNA origami enables the precise fabrication of nanoscale geometries. We demonstrate an approach to engineer complex and reversible motion of nanoscale DNA origami machine elements. We first design, fabricate, and characterize the mechanical behavior of flexible DNA origami rotational and linear joints that integrate stiff double-stranded DNA components and flexible single-stranded DNA components to constrain motion along a single degree of freedom and demonstrate the ability to tune the flexibility and range of motion. Multiple joints with simple 1D motion were then integrated into higher order mechanisms. One mechanism is a crank–slider that couples rotational and linear motion, and the other is a Bennett linkage that moves between a compacted bundle and an expanded frame configuration with a constrained 3D motion path. Finally, we demonstrate distributed actuation of the linkage using DNA input strands to achieve reversible conformational changes of the entire structure on ∼minute timescales. Our results demonstrate programmable motion of 2D and 3D DNA origami mechanisms constructed following a macroscopic machine design approach.The ability to control, manipulate, and organize matter at the nanoscale has demonstrated immense potential for advancements in industrial technology, medicine, and materials (1–3). Bottom-up self-assembly has become a particularly promising area for nanofabrication (4, 5); however, to date designing complex motion at the nanoscale remains a challenge (6–9). Amino acid polymers exhibit well-defined and complex dynamics in natural systems and have been assembled into designed structures including nanotubes, sheets, and networks (10–12), although the complexity of interactions that govern amino acid folding make designing complex geometries extremely challenging. DNA nanotechnology, on the other hand, has exploited well-understood assembly properties of DNA to create a variety of increasingly complex designed nanostructures (13–15).Scaffolded DNA origami, the process of folding a long single-stranded DNA (ssDNA) strand into a custom structure (16–18), has enabled the fabrication of nanoscale objects with unprecedented geometric complexity that have recently been implemented in applications such as containers for drug delivery (19, 20), nanopores for single-molecule sensing (21–23), and templates for nanoparticles (24, 25) or proteins (26–28). The majority of these and other applications of DNA origami have largely focused on static structures. Natural biomolecular machines, in contrast, have a rich diversity of functionalities that rely on complex but well-defined and reversible conformational changes. Currently, the scope of biomolecular nanotechnology is limited by an inability to achieve similar motion in designed nanosystems.DNA nanotechnology has enabled critical steps toward that goal starting with the work of Mao et al. (29), who developed a DNA nanostructure that took advantage of the B–Z transition of DNA to switch states. Since then, efforts to fabricate dynamic DNA systems have primarily focused on strand displacement approaches (30) mainly on systems comprising a few strands or arrays of strands undergoing ∼nm-scale motions (31–37) in some cases guided by DNA origami templates (38–40). More recently, strand displacement has been used to reconfigure DNA origami nanostructures, for example opening DNA containers (19, 41, 42), controlling molecular binding (43, 44), or reconfiguring structures (45). The largest triggerable structural change was achieved by Han et al. in a DNA origami Möbius strip (one-sided ribbon structure) that could be opened to approximately double in size (45). Constrained motion has been achieved in systems with rotational motion (19, 20, 32, 41, 44, 46, 47) in some cases to open lid-like components (19, 20, 41) or detect molecular binding (44, 48, 49). A few of these systems achieved reversible conformational changes (32, 41, 44, 46), although the motion path and flexibility were not studied. Constrained linear motion has remained largely unexplored. Linear displacements on the scale of a few nanometers have been demonstrated via conformational changes of DNA structure motifs (50–55), strand invasion to open DNA hairpins (36, 55, 56), or the reversible sliding motion of a DNA tile actuator (56); these cases also did not investigate the motion path or flexibility of motion.Building on these prior studies, this work implements concepts from macroscopic machine design to build modular parts with constrained motion. We demonstrate an ability to tune the flexibility and range of motion and then integrate these parts into prototype mechanisms with designed 2D and 3D motion. We further demonstrate reversible actuation of a mechanism with complex conformational changes on minute timescales.     

Self-assembly of alkynylplatinum(II) terpyridine amphiphiles into nanostructures via steric control and metal–metal interactions

A series of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing the hydrophilic oligo(para-phenylene ethynylene) with two 3,6,9-trioxadec-1-yloxy chains was designed and synthesized. The mononuclear alkynylplatinum(II) terpyridine complex was found to display a very strong tendency toward the formation of supramolecular structures. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would lead to the formation of nanotubes or helical ribbons. These desirable nanostructures were found to be governed by the steric bulk on the platinum(II) terpyridine moieties, which modulates the directional metal−metal interactions and controls the formation of nanotubes or helical ribbons. Detailed analysis of temperature-dependent UV-visible absorption spectra of the nanostructured tubular aggregates also provided insights into the assembly mechanism and showed the role of metal−metal interactions in the cooperative supramolecular polymerization of the amphiphilic platinum(II) complexes.Square-planar d⁸ platinum(II) polypyridine complexes have long been known to exhibit intriguing spectroscopic and luminescence properties (1–54) as well as interesting solid-state polymorphism associated with metal−metal and π−π stacking interactions (1–14, 25). Earlier work by our group showed the first example, to our knowledge, of an alkynylplatinum(II) terpyridine system [Pt(tpy)(C ≡ CR)]⁺ that incorporates σ-donating and solubilizing alkynyl ligands together with the formation of Pt···Pt interactions to exhibit notable color changes and luminescence enhancements on solvent composition change (25) and polyelectrolyte addition (26). This approach has provided access to the alkynylplatinum(II) terpyridine and other related cyclometalated platinum(II) complexes, with functionalities that can self-assemble into metallogels (27–31), liquid crystals (32, 33), and other different molecular architectures, such as hairpin conformation (34), helices (35–38), nanostructures (39–45), and molecular tweezers (46, 47), as well as having a wide range of applications in molecular recognition (48–52), biomolecular labeling (48–52), and materials science (53, 54). Recently, metal-containing amphiphiles have also emerged as a building block for supramolecular architectures (42–44, 55–59). Their self-assembly has always been found to yield different molecular architectures with unprecedented complexity through the multiple noncovalent interactions on the introduction of external stimuli (42–44, 55–59).Helical architecture is one of the most exciting self-assembled morphologies because of the uniqueness for the functional and topological properties (60–69). Helical ribbons composed of amphiphiles, such as diacetylenic lipids, glutamates, and peptide-based amphiphiles, are often precursors for the growth of tubular structures on an increase in the width or the merging of the edges of ribbons (64, 65). Recently, the optimization of nanotube formation vs. helical nanostructures has aroused considerable interests and can be achieved through a fine interplay of the influence on the amphiphilic property of molecules (66), choice of counteranions (67, 68), or pH values of the media (69), which would govern the self-assembly of molecules into desirable aggregates of helical ribbons or nanotube scaffolds. However, a precise control of supramolecular morphology between helical ribbons and nanotubes remains challenging, particularly for the polycyclic aromatics in the field of molecular assembly (64–69). Oligo(para-phenylene ethynylene)s (OPEs) with solely π−π stacking interactions are well-recognized to self-assemble into supramolecular system of various nanostructures but rarely result in the formation of tubular scaffolds (70–73). In view of the rich photophysical properties of square-planar d⁸ platinum(II) systems and their propensity toward formation of directional Pt···Pt interactions in distinctive morphologies (27–31, 39–45), it is anticipated that such directional and noncovalent metal−metal interactions might be capable of directing or dictating molecular ordering and alignment to give desirable nanostructures of helical ribbons or nanotubes in a precise and controllable manner.Herein, we report the design and synthesis of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing hydrophilic OPEs with two 3,6,9-trioxadec-1-yloxy chains. The mononuclear alkynylplatinum(II) terpyridine complex with amphiphilic property is found to show a strong tendency toward the formation of supramolecular structures on diffusion of diethyl ether in dichloromethane or dimethyl sulfoxide (DMSO) solution. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would result in nanotubes or helical ribbons in the self-assembly process. To the best of our knowledge, this finding represents the first example of the utilization of the steric bulk of the moieties, which modulates the formation of directional metal−metal interactions to precisely control the formation of nanotubes or helical ribbons in the self-assembly process. Application of the nucleation–elongation model into this assembly process by UV-visible (UV-vis) absorption spectroscopic studies has elucidated the nature of the molecular self-assembly, and more importantly, it has revealed the role of metal−metal interactions in the formation of these two types of nanostructures.     

Exchange protein directly activated by cAMP plays a critical role in bacterial invasion during fatal rickettsioses

Rickettsiae are responsible for some of the most devastating human infections. A high infectivity and severe illness after inhalation make some rickettsiae bioterrorism threats. We report that deletion of the exchange protein directly activated by cAMP (Epac) gene, Epac1, in mice protects them from an ordinarily lethal dose of rickettsiae. Inhibition of Epac1 suppresses bacterial adhesion and invasion. Most importantly, pharmacological inhibition of Epac1 in vivo using an Epac-specific small-molecule inhibitor, ESI-09, completely recapitulates the Epac1 knockout phenotype. ESI-09 treatment dramatically decreases the morbidity and mortality associated with fatal spotted fever rickettsiosis. Our results demonstrate that Epac1-mediated signaling represents a mechanism for host–pathogen interactions and that Epac1 is a potential target for the prevention and treatment of fatal rickettsioses.Rickettsiae are responsible for some of the most devastating human infections (1–4). It has been forecasted that temperature increases attributable to global climate change will lead to more widespread distribution of rickettsioses (5). These tick-borne diseases are caused by obligately intracellular bacteria of the genus Rickettsia, including Rickettsia rickettsii, the causative agent of Rocky Mountain spotted fever (RMSF) in the United States and Latin America (2, 3), and Rickettsia conorii, the causative agent of Mediterranean spotted fever endemic to southern Europe, North Africa, and India (6). A high infectivity and severe illness after inhalation make some rickettsiae (including Rickettsia prowazekii, R. rickettsii, Rickettsia typhi, and R. conorii) bioterrorism threats (7). Although the majority of rickettsial infections can be controlled by appropriate broad-spectrum antibiotic therapy if diagnosed early, up to 20% of misdiagnosed or untreated (1, 3) and 5% of treated RMSF cases (8) result in a fatal outcome caused by acute disseminated vascular endothelial infection and damage (9). Fatality rates as high as 32% have been reported in hospitalized patients diagnosed with Mediterranean spotted fever (10). In addition, strains of R. prowazekii resistant to tetracycline and chloramphenicol have been developed in laboratories (11). Disseminated endothelial infection and endothelial barrier disruption with increased microvascular permeability are the central features of SFG rickettsioses (1, 2, 9). The molecular mechanisms involved in rickettsial infection remain incompletely elucidated (9, 12). A comprehensive understanding of rickettsial pathogenesis and the development of novel mechanism-based treatment are urgently needed.Living organisms use intricate signaling networks for sensing and responding to changes in the external environment. cAMP, a ubiquitous second messenger, is an important molecular switch that translates environmental signals into regulatory effects in cells (13). As such, a number of microbial pathogens have evolved a set of diverse virulence-enhancing strategies that exploit the cAMP-signaling pathways of their hosts (14). The intracellular functions of cAMP are predominantly mediated by the classic cAMP receptor, protein kinase A (PKA), and the more recently discovered exchange protein directly activated by cAMP (Epac) (15). Thus, far, two isoforms, Epac1 and Epac2, have been identified in humans (16, 17). Epac proteins function by responding to increased intracellular cAMP levels and activating the Ras superfamily small GTPases Ras-proximate 1 and 2 (Rap1 and Rap2). Accumulating evidence demonstrates that the cAMP/Epac1 signaling axis plays key regulatory roles in controlling various cellular functions in endothelial cells in vitro, including cell adhesion (18–21), exocytosis (22), tissue plasminogen activator expression (23), suppressor of cytokine signaling 3 (SOCS-3) induction (24–27), microtubule dynamics (28, 29), cell–cell junctions, and permeability and barrier functions (30–37). Considering the critical importance of endothelial cells in rickettsioses, we examined the functional roles of Epac1 in rickettsial pathogenesis in vivo, taking advantage of the recently generated Epac1 knockout mouse (38) and Epac-specific inhibitors (39, 40) generated from our laboratory. Our studies demonstrate that Epac1 plays a key role in rickettsial infection and represents a therapeutic target for fatal rickettsioses.     

From the Cover: Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Antiretroviral therapy (ART) reduces the infectiousness of HIV-infected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection (“early transmission”) is perceived as a threat to the impact of HIV “treatment-as-prevention” strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate—consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R₀) are consistent with observed epidemic growth, and R₀ was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.Recent studies have confirmed that effective antiretroviral therapy (ART) reduces the transmission of HIV among stable heterosexual couples (1–3). This finding has generated interest in understanding the population-level impact of HIV treatment on reducing the rate of new HIV infections in generalized epidemic settings (4). Research, including mathematical modeling (5–10), implementation research (11), and major randomized controlled trials (12–14), are focused on how ART provision might be expanded strategically to maximize its public health benefits (15, 16).One concern is that if a large fraction of HIV transmission occurs shortly after a person becomes infected, before the person can be diagnosed and initiated on ART, this will limit the potential impact of HIV treatment on reducing HIV incidence (9, 17, 18). Data suggest that persons are more infectious during a short period of “early infection” after becoming infected with HIV (19–22), although there is debate about the extent, duration, and determinants of elevated infectiousness (18, 23). The amount of transmission that occurs also will depend on patterns of sexual behavior and sexual networks (17, 24–27). There have been estimates for the contribution of early infection to transmission from mathematical models (7, 17, 21, 24–26) and phylogenetic analyses (28–31), but these vary widely, from 5% to above 50% (23).In this study, we use a mathematical model to quantify how the proportion of transmission that comes from persons who have been infected recently affects the impact of treatment scale-up on HIV incidence. The model is calibrated to longitudinal HIV prevalence data from South Africa using a Bayesian framework. Thus, the model accounts for not only the early epidemic growth rate highlighted in previous research (5, 9, 18), but also the heterogeneity and sexual behavior change to explain the peak and decline in HIV incidence observed in sub-Saharan African HIV epidemics (32, 33).The model calibration allows uncertainty about factors that determine the amount of early transmission, including the relative infectiousness during early infection, heterogeneity in propensity for sexual risk behavior, assortativity in sexual partner selection, reduction in risk propensity over the life course, and population-wide reductions in risk behavior in response to the epidemic (32, 33). This results in multiple combinations of parameter values that are consistent with the observed epidemic and variation in the amount of early transmission. We simulated the impact of a treatment intervention and report how the proportion of early transmission correlates with the reduction in HIV incidence from the intervention over the short- and long-term.     

Transition paths,diffusive processes,and preequilibria of protein folding

Fundamental relationships between the thermodynamics and kinetics of protein folding were investigated using chain models of natural proteins with diverse folding rates by extensive comparisons between the distribution of conformations in thermodynamic equilibrium and the distribution of conformations sampled along folding trajectories. Consistent with theory and single-molecule experiment, duration of the folding transition paths exhibits only a weak correlation with overall folding time. Conformational distributions of folding trajectories near the overall thermodynamic folding/unfolding barrier show significant deviations from preequilibrium. These deviations, the distribution of transition path times, and the variation of mean transition path time for different proteins can all be rationalized by a diffusive process that we modeled using simple Monte Carlo algorithms with an effective coordinate-independent diffusion coefficient. Conformations in the initial stages of transition paths tend to form more nonlocal contacts than typical conformations with the same number of native contacts. This statistical bias, which is indicative of preferred folding pathways, should be amenable to future single-molecule measurements. We found that the preexponential factor defined in the transition state theory of folding varies from protein to protein and that this variation can be rationalized by our Monte Carlo diffusion model. Thus, protein folding physics is different in certain fundamental respects from the physics envisioned by a simple transition-state picture. Nonetheless, transition state theory can be a useful approximate predictor of cooperative folding speed, because the height of the overall folding barrier is apparently a proxy for related rate-determining physical properties.Protein folding is an intriguing phenomenon at the interface of physics and biology. In the early days of folding kinetics studies, folding was formulated almost exclusively in terms of mass-action rate equations connecting the folded, unfolded, and possibly, one or a few intermediate states (1, 2). With the advent of site-directed mutagenesis, the concept of free energy barriers from transition state theory (TST) (3) was introduced to interpret mutational data (4), and subsequently, it was adopted for the Φ-value analysis (5). Since the 1990s, the availability of more detailed experimental data (6), in conjunction with computational development of coarse-grained chain models, has led to an energy landscape picture of folding (7–15). This perspective emphasizes the diversity of microscopic folding trajectories, and it conceptualizes folding as a diffusive process (16–25) akin to the theory of Kramers (26).For two-state-like folding, the transition path (TP), i.e., the sequence of kinetic events that leads directly from the unfolded state to the folded state (27, 28), constitutes only a tiny fraction of a folding trajectory that spends most of the time diffusing, seemingly unproductively, in the vicinity of the free energy minimum of the unfolded state. The development of ultrafast laser spectroscopy (29, 30) and single-molecule (27, 28, 31) techniques have made it possible to establish upper bounds on the transition path time (t_TP) ranging from <200 and <10 μs by earlier (27) and more recent (28), respectively, direct single-molecule FRET to <2 μs (30) by bulk relaxation measurements. Consistent with these observations, recent extensive atomic simulations have also provided estimated t_TP values of the order of ∼1 μs (32, 33). These advances offer exciting prospects of characterizing the productive events along folding TPs.It is timely, therefore, to further the theoretical investigation of TP-related questions (19). To this end, we used coarse-grained C_α models (14) to perform extensive simulations of the folding trajectories of small proteins with 56- to 86-aa residues. These tractable models are useful, because despite significant progress, current atomic models cannot provide the same degree of sampling coverage for proteins of comparable sizes (32, 33). In addition to structural insights, this study provides previously unexplored vantage points to compare the diffusion and TST pictures of folding. Deviations of folding behaviors from TST predictions are not unexpected, because TST is mostly applicable to simple gas reactions; however, the nature and extent of the deviations have not been much explored. Our explicit-chain simulation data conform well to the diffusion picture but not as well to TST. In particular, the preexponential factors of the simulated folding rates exhibit a small but appreciable variation that depends on native topology. These findings and others reported below underscore the importance of single-molecule measurements (13, 27, 28, 31, 34, 35) in assessing the merits of proposed scenarios and organizing principles of folding (7–25, 36, 37).