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Single-particle electron cryo-microscopy (cryoEM) has undergone a “resolution revolution” that makes it possible to characterize megadalton (MDa) complexes at atomic resolution without crystals. To fully exploit the new opportunities in molecular microscopy, new procedures for the cloning, expression and purification of macromolecular complexes need to be explored. Macromolecular assemblies are often unstable, and invasive construct design or inadequate purification conditions or sample preparation methods can result in disassembly or denaturation. The structure of the 2.6 MDa yeast fatty acid synthase (FAS) has been studied by electron microscopy since the 1960s. We report a new, streamlined protocol for the rapid production of purified yeast FAS for structure determination by high-resolution cryoEM. Together with a companion protocol for preparing cryoEM specimens on a hydrophilized graphene layer, our new protocol has yielded a 3.1 Å map of yeast FAS from 15,000 automatically picked particles within a day. The high map quality enabled us to build a complete atomic model of an intact fungal FAS.
Engineering of assembly line polyketide synthases (PKSs) to produce novel bioactive compounds has been a goal for over twenty years. The apparent modularity of PKSs has inspired many engineering attempts in which entire modules or single domains were exchanged. In recent years, it has become evident that certain domain-domain interactions are evolutionarily optimized, and if disrupted, cause a decrease of the overall turnover rate of the chimeric PKS. In this study, we compared different types of chimeric PKSs in order to define the least invasive interface and to expand the toolbox for PKS engineering. We generated bimodular chimeric PKSs in which entire modules were exchanged, while either retaining a covalent linker between heterologous modules or introducing a non-covalent docking domain- or SYNZIP domain-mediated interface. These chimeric systems exhibited non-native domain-domain interactions during intermodular polyketide chain translocation. They were compared to otherwise equivalent bimodular PKSs in which a non-covalent interface was introduced between the condensing and processing parts of a module, resulting in non-native domain interactions during the extender unit acylation and polyketide chain elongation steps of their catalytic cycles. We show that the natural PKS docking domains can be efficiently substituted with SYNZIP domains and that the newly introduced non-covalent interface between the condensing and processing parts of a module can be harnessed for PKS engineering. Additionally, we established SYNZIP domains as a new tool for engineering PKSs by efficiently bridging non-native interfaces without perturbing PKS activity.
The cortical networks that underlie behavior exhibit an orderly functional organization at local and global scales, which is readily evident in the visual cortex of carnivores and primates1-6. Here, neighboring columns of neurons represent the full range of stimulus orientations and contribute to distributed networks spanning several millimeters2,7-11. However, the principles governing functional interactions that bridge this fine-scale functional architecture and distant network elements are unclear, and the emergence of these network interactions during development remains unexplored. Here, by using in vivo wide-field and 2-photon calcium imaging of spontaneous activity patterns in mature ferret visual cortex, we find widespread and specific modular correlation patterns that accurately predict the local structure of visually-evoked orientation columns from the spontaneous activity of neurons that lie several millimeters away. The large-scale networks revealed by correlated spontaneous activity show abrupt ‘fractures’ in continuity that are in tight register with evoked orientation pinwheels. Chronic in vivo imaging demonstrates that these large-scale modular correlation patterns and fractures are already present at early stages of cortical development and predictive of the mature network structure. Silencing feed-forward drive through either retinal or thalamic blockade does not affect network structure suggesting a cortical origin for this large-scale correlated activity, despite the immaturity of long-range horizontal network connections in the early cortex. Using a circuit model containing only local connections, we demonstrate that such a circuit is sufficient to generate large-scale correlated activity, while also producing correlated networks showing strong fractures, a reduced dimensionality, and an elongated local correlation structure, all in close agreement with our empirical data. These results demonstrate the precise local and global organization of cortical networks revealed through correlated spontaneous activity and suggest that local connections in early cortical circuits may generate structured long-range network correlations that underlie the subsequent formation of visually-evoked distributed functional networks.
Autosomal recessive Ataxia Telangiectasia (A-T) is characterized by radiosensitivity, immunodeficiency and cerebellar neurodegeneration. A-T is caused by inactivating mutations in the Ataxia-Telangiectasia-Mutated (ATM) gene, a serine-threonine protein kinase involved in DNA-damage response and excitatory neurotransmission. The selective vulnerability of cerebellar Purkinje neurons (PN) to A-T is not well understood.
A key event in cellular physiology is the decision between membrane biogenesis and fat storage. Phosphatidic acid (PA) is an important intermediate at the branch point of these pathways and is continuously monitored by the transcriptional repressor Opi1 to orchestrate lipid metabolism. In this study, we report on the mechanism of membrane recognition by Opi1 and identify an amphipathic helix (AH) for selective binding of PA over phosphatidylserine (PS). The insertion of the AH into the membrane core renders Opi1 sensitive to the lipid acyl chain composition and provides a means to adjust membrane biogenesis. By rational design of the AH, we tune the membrane-binding properties of Opi1 and control its responsiveness in vivo. Using extensive molecular dynamics simulations, we identify two PA-selective three-finger grips that tightly bind the PA phosphate headgroup while interacting less intimately with PS. This work establishes lipid headgroup selectivity as a new feature in the family of AH-containing membrane property sensors.
A key event in cellular physiology is the decision between membrane biogenesis and fat storage. Phosphatidic acid (PA) is an important lipid intermediate and signaling lipid at the branch point of these pathways and constantly monitored by the transcriptional repressor Opi1 to orchestrate lipid metabolism. Here, we report on the mechanism of membrane recognition by Opi1 and identify an amphipathic helix (AH) for the selective binding to membranes containing PA over phosphatidylserine (PS). The insertion of the AH into the hydrophobic core of the membrane renders Opi1 sensitive to the lipid acyl chain composition as an important factor contributing to the regulation of membrane biogenesis. Based on these findings, we rationally designed the membrane binding properties of Opi1 to control its responsiveness in the physiological context. Using extensive molecular dynamics (MD) simulations, we identified two PA-selective three-finger grips that tightly bind the phosphate headgroup, while interacting less intimately and more transiently with PS. This work establishes lipid headgroup selectivity as a new feature in the family of AH-containing membrane property sensors.
The basidiomycete smut fungi are predominantly plant parasitic, causing severe losses in some crops. Most species feature a saprotrophic haploid yeast stage, and several smut fungi are only known from this stage, with some isolated from habitats without suitable hosts, e.g. from Antarctica. Thus, these species are generally believed to be apathogenic, but recent findings that some of these might have a plant pathogenic sexual counterpart, casts doubts on the validity of this hypothesis. Here, four Pseudozyma genomes were re-annotated and compared to published smut pathogens and the well-characterised effector gene Pep1 from these species was checked for its ability to complement a Pep1 deletion strain of Ustilago maydis. It was found that 113 high-confidence putative effector proteins were conserved among smut and Pseudozyma genomes. Among these were several validated effector proteins, including Pep1. By genetic complementation we show that Pep1 homologs from the supposedly apathogenic yeasts restore virulence in Pep1-deficient mutants Ustilago maydis. Thus, it is concluded that Pseudozyma species have retained a suite of effectors. This hints at the possibility that Pseudozyma species have kept an unknown plant pathogenic stage for sexual recombination or that these effectors have positive effects when colonising plant surfaces.
The gradual heterogeneity of climatic factors pose varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift, and adaptation to non-clinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool-Seq data, and population genetic modelling. Common-garden experiments revealed a positive correlation of population growth rates corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an FST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in other studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.
One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.
All giraffe (Giraffa) were previously assigned to a single species (G. Camelopardalis) and nine subspecies. However, multi-locus analyses of all subspecies have shown that there are four genetically distinct clades and suggest four giraffe species. This conclusion might not be fully accepted due to limited data and lack of explicit gene flow analyses. Here we present an extended study based on 21 independent nuclear loci from 137 individuals. Explicit gene flow analyses identify less than one migrant per generation, including between the closely related northern and reticulated giraffe. Thus, gene flow analyses and population genetics of the extended dataset confirm four genetically distinct giraffe clades and support four independent giraffe species. The new findings call for a revision of the IUCN classification of giraffe taxonomy. Three of the four species are threatened with extinction, mostly occurring in politically unstable regions, and as such, require the highest conservation support possible.
The debate on effects of globalization on welfare states is extensive. Often couched in terms of a battle between the compensation and the efficiency thesis, the scholarly literature has provided contradictory arguments and findings. This article contributes to the scholarly debate by exploring in greater detail the micro-level foundations of compensation theory. More specifically, we distinguish between individual policy preferences for compensatory social policies (unemployment insurance) and human capital-focused social investment policies (education) and expect globalization to mainly affect demand for educational investment. A multi-level analysis of ISSP survey data provides empirical support for this hypothesis. This finding provides an important revision and extension of the classical analytical perspective of compensation theory, because it shows that citizens value the social investment function of the welfare state above and beyond simple compensation via social transfers. This might be particularly relevant in today's skill-centered knowledge economies.
Interest in time-resolved connectivity in fMRI has grown rapidly in recent years. The most widely used technique for studying connectivity changes over time utilizes a sliding windows approach. There has been some debate about the utility of shorter versus longer windows, the use of fixed versus adaptive windows, as well as whether observed resting state dynamics during wakefulness may be predominantly due to changes in sleep state and subject head motion. In this work we use an independent component analysis (ICA)-based pipeline applied to concurrent EEG/fMRI data collected during wakefulness and various sleep stages and show: 1) connectivity states obtained from clustering sliding windowed correlations of resting state functional network time courses well classify the sleep states obtained from EEG data, 2) using shorter sliding windows instead of longer non-overlapping windows improves the ability to capture transition dynamics even at windows as short as 30 seconds, 3) motion appears to be mostly associated with one of the states rather than spread across all of them 4) a fixed tapered sliding window approach outperforms an adaptive dynamic conditional correlation approach, and 5) consistent with prior EEG/fMRI work, we identify evidence of multiple states within the wakeful condition which are able to be classified with high accuracy. Classification of wakeful only states suggest the presence of time-varying changes in connectivity in fMRI data beyond sleep state or motion. Results also inform about advantageous technical choices, and the identification of different clusters within wakefulness that are separable suggest further studies in this direction.
Summary statement When echolocating under demanding conditions e.g. noisy, narrow space, or cluttered environments, frugivorous bats adapt their call pattern by increasing the call rate within biosonar groups.
Abstract For orientation, echolocating bats emit biosonar calls and use echoes arising from call reflections. They often pattern their calls into groups which increases the rate of sensory feedback over time. Insectivorous bats emit call groups at a higher rate when orienting in cluttered compared to uncluttered environments. Frugivorous bats increase the rate of call group emission when they echolocate in noisy environments. Here, calls emitted by conspecifics potentially interfere with the bat’s biosonar signals and complicate the echolocation behavior. To minimize the information loss followed by signal interference, bats may profit from a temporally increased sensory acquisition rate, as it is the case for the call groups. In frugivorous bats, it remains unclear if call group emission represents an exclusive adaptation to avoid interference by signals from other bats or if it represents an adaptation that allows to orient under demanding environmental conditions. Here, we compared the emission pattern of the frugivorous bat Carollia perspicillata when the bats were flying in noisy versus silent, narrow versus wide or cluttered versus non-cluttered corridors. According to our results, the bats emitted larger call groups and they increased the call rate within the call groups when navigating in narrow, cluttered, or noisy environments. Thus, call group emission represents an adaptive behavior when the bats orient in complex environments.
The outstanding speed of language comprehension necessitates a highly efficient implementation of cognitive-linguistic processes. The domain-general theory of Predictive Coding suggests that our brain solves this problem by continuously forming linguistic predictions about expected upcoming input. The neurophysiological implementation of these predictive linguistic processes, however, is not yet understood. Here, we use EEG (human participants, both sexes) to investigate the existence and nature of online-generated, category-level semantic representations during sentence processing. We conducted two experiments in which some nouns – embedded in a predictive spoken sentence context – were unexpectedly delayed by 1 second. Target nouns were either abstract/concrete (Experiment 1) or animate/inanimate (Experiment 2). We hypothesized that if neural prediction error signals following (temporary) omissions carry specific information about the stimulus, the semantic category of the upcoming target word is encoded in brain activity prior to its presentation. Using time-generalized multivariate pattern analysis, we demonstrate significant decoding of word category from silent periods directly preceding the target word, in both experiments. This provides direct evidence for predictive coding during sentence processing, i.e., that information about a word can be encoded in brain activity before it is perceived. While the same semantic contrast could also be decoded from EEG activity elicited by isolated words (Experiment 1), the identified neural patterns did not generalize to pre-stimulus delay period activity in sentences. Our results not only indicate that the brain processes language predictively, but also demonstrate the nature and sentence-specificity of category-level semantic predictions preactivated during sentence comprehension.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. Orthologous genes that are detected across the full diversity of contemporary life allow reconstructing the gene set of LUCA, the last universal common ancestor. These genes presumably represent the functional repertoire common to – and necessary for – all living organisms. Design of artificial life has the potential to test this. Recently, a minimal gene (MG) set for a self-replicating cell was determined experimentally, and a surprisingly high number of genes have unknown functions and are not represented in LUCA. However, as similarity between orthologs decays with time, it becomes insufficient to infer common ancestry, leaving ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the evolutionary traceability, together with the software protTrace, that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. We show that the LUCA set comprises only high-traceable proteins most of which have catalytic functions. We further show that proteins in the MG set lacking orthologs outside bacteria mostly have low traceability, leaving open whether their eukaryotic orthologs have just been overlooked. On the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and non-detection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks.
Stockpiling neuraminidase inhibitors (NAIs) such as oseltamivir and zanamivir is part of a global effort to be prepared for an influenza pandemic. However, the contribution of NAIs for treatment and prevention of influenza and its complications is largely debatable. Here, we developed a transparent mathematical modelling setting to analyse the impact of NAIs on influenza disease at within-host and population level. Analytical and simulation results indicate that even assuming unrealistically high efficacies for NAIs, drug intake starting on the onset of symptoms has a negligible effect on an individual's viral load and symptoms score. Increasing NAIs doses does not provide a better outcome as is generally believed. Considering Tamiflu's pandemic regimen for prophylaxis, different multiscale simulation scenarios reveal modest reductions in epidemic size despite high investments in stockpiling. Our results question the use of NAIs in general to treat influenza as well as the respective stockpiling by regulatory authorities.
The successful elimination of bacteria such as Streptococcus pneumoniae from a host involves the coordination between different parts of the immune system. Previous studies have explored the effects of the initial pneumococcal load (bacterial dose) on different representations of innate immunity, finding that pathogenic outcomes can vary with the size of the bacterial dose. However, others yield support to the notion of dose-independent factors contributing to bacterial clearance. In this paper, we seek to provide a deeper understanding of the immune responses associated to the pneumococcus. To this end, we formulate a model that realizes an abstraction of the innate-regulatory immune host response. Stability and bifurcation analyses of the model reveal the following trichotomy of pneumococcal outcomes determined by the bifurcation parameters: (i) dose-independent clearance; (ii) dose-independent persistence; and (iii) dose-limited clearance. Bistability, where the bacteria-free equilibrium co-stabilizes with the most substantial steady-state bacterial load is the specific result behind dose-limited clearance. The trichotomy of pneumococcal outcomes here described integrates all previously observed bacterial fates into a unified framework.
Background Corticospinal excitability depends on the current brain state. The recent development of real-time EEG-triggered transcranial magnetic stimulation (EEG-TMS) allows studying this relationship in a causal fashion. Specifically, it has been shown that corticospinal excitability is higher during the scalp surface negative EEG peak compared to the positive peak of µ-oscillations in sensorimotor cortex, as indexed by larger motor evoked potentials (MEPs) for fixed stimulation intensity.
Objective We further characterize the effect of µ-rhythm phase on the MEP input-output (IO) curve by measuring the degree of excitability modulation across a range of stimulation intensities. We furthermore seek to optimize stimulation parameters to enable discrimination of functionally relevant EEG-defined brain states.
Methods A real-time EEG-TMS system was used to trigger MEPs during instantaneous brain-states corresponding to µ-rhythm surface positive and negative peaks with five different stimulation intensities covering an individually calibrated MEP IO curve in 15 healthy participants.
Results MEP amplitude is modulated by µ-phase across a wide range of stimulation intensities, with larger MEPs at the surface negative peak. The largest relative MEP-modulation was observed for weak intensities, the largest absolute MEP-modulation for intermediate intensities. These results indicate a leftward shift of the MEP IO curve during the µ-rhythm negative peak.
Conclusion The choice of stimulation intensity influences the observed degree of corticospinal excitability modulation by µ-phase. Lower stimulation intensities enable more efficient differentiation of EEG µ-phase-defined brain states.