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PMCE: efficient inference of expressive models of cancer evolution with high prognostic power MotivationDriver (epi)genomic alterations underlie the positive selection of cancer subpopulations, which promotes drug resistance and relapse. Even though substantial heterogeneity is witnessed in most cancer types, mutation accumulation patterns can be regularly found and can be exploited to reconstruct predictive models of cancer evolution. Yet, available methods cannot infer logical formulas connecting events to represent alternative evolutionary routes or convergent evolution.
ResultsWe introduce PMCE, an expressive framework that leverages mutational profiles from crosssectional sequencing data to infer probabilistic graphical models of cancer evolution including arbitrary logical formulas, and which outperforms the state-of-the-art in terms of accuracy and robustness to noise, on simulations.
The application of PMCE to 7866 samples from the TCGA database allows us to identify a highly significant correlation between the predicted evolutionary paths and the overall survival in 7 tumor types, proving that our approach can effectively stratify cancer patients in reliable risk groups.
AvailabilityPMCE is freely available at https://github.com/BIMIB-DISCo/PMCE, in addition to the code to replicate all the analyses presented in the manuscript.
[email protected], [email protected]. | bioinformatics |
Convergent evolution of primate testis transcriptomes reflects mating strategy In independent mammalian lineages where females mate with multiple males (multi-male mating strategies), males have evolved larger testicles relative to those lineages where females mate with fewer males (single-male mating strategies). Here we study published bulk testis transcriptomes from humans, chimpanzees, gorillas and rhesus macaques, as well as mice and rats. Employing a formal model of adaptive evolution, we find that testis transcriptomes have also evolved convergently, reflecting each species mating strategy. Using deconvolution, we infer that testis transcriptome divergence patterns largely reflect convergent shifts in tissue cell type composition. However, we also identify modest amounts of convergent evolution at the cell-autonomous level by analyzing cell-type specific transcriptome data from spermatids and spermatocytes. We further show that in the single-male mating primates, human and gorilla, testis transcriptome profiles are paedomorphic relative to those of multi-male primates, chimpanzee and macaque, suggesting that shifts in timing or rate of testis development could underlie convergent changes in testis mass, histology, and transcriptomes. | evolutionary biology |
A max-margin model for predicting residue-base contacts in protein-RNA interactions Protein-RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex protein-RNA structures, various computational methods have been developed to predict PRIs. However, most of these methods focus on predicting only RNA-binding regions in proteins or only protein-binding motifs in RNA. Methods for predicting entire residue-base contacts in PRIs have not yet achieved sufficient accuracy. Furthermore, some of these methods require the identification of 3D structures or homologous sequences, which are not available for all protein and RNA sequences. Here, we propose a prediction method for predicting residue-base contacts between proteins and RNAs using only sequence information and structural information predicted from sequences. The method can be applied to any protein-RNA pair, even when rich information such as its 3D structure, is not available. In this method, residue-base contact prediction is formalized as an integer programming problem. We predict a residue-base contact map that maximizes a scoring function based on sequence-based features such as k-mers of sequences and the predicted secondary structure. The scoring function is trained using a max-margin framework from known PRIs with 3D structures. To verify our method, we conducted several computational experiments. The results suggest that our method, which is based on only sequence information, is comparable with RNA-binding residue prediction methods based on known binding data. | bioinformatics |
Engineered acetoacetate-inducible whole-cell biosensors based on the AtoSC two-component system Whole-cell biosensors hold potential in a variety of industrial, medical and environmental applications. These biosensors can be constructed through the repurposing of bacterial sensing mechanisms, including the common two-component system. Here we report on the construction of a range of novel biosensors that are sensitive to acetoacetate, a molecule that plays a number of roles in human health and biology. These biosensors are based on the AtoSC two-component system. An ODE model to describe the action of the AtoSC two-component system was developed and sensitivity analysis of this model used to help inform biosensor design. The final collection of biosensors constructed displayed a range of switching behaviours, at physiologically relevant acetoacetate concentrations and can operate in several Escherichia coli host strains. It is envisaged that these biosensor strains will offer an alternative to currently available commercial strip tests and, in future, may be adopted for more complex in vivo or industrial monitoring applications. | synthetic biology |
Association of NQO1 C609T (Pro187Ser) with risk of Oral Submucous Fibrosis in Eastern Indian population Oral submucous fibrosis (OSF) is a debilitating disease mainly attributed to chewing areca nut with a 7.4-13% malignant transformation rate. Present study explores the role of NADPH quinone oxidoreductase 1 (NQO1) C609T (Pro187Ser) polymorphism in susceptibility to OSF among habitual areca nut chewers in an eastern Indian population. Overall, about 18% of the total OSF cases were detected carrying minor TT allele (Ser/Ser) p=0.026. When categorized by age, both CT (Pro/Ser) and TT (Ser/Ser) alleles were significantly higher (p= 0.003 & 0.004 respectively) in cases above 40years of age. NQO1 protein was 42% reduced in buccal tissues of heterozygous (Pro/Ser) carriers, whereas a 70% reduction was observed in TT (Ser/Ser) OSF cases. Our study suggests that the NQO1 C609T polymorphism confers increased risk for OSF in habitual chewers. | genetics |
Fast gene set enrichment analysis Gene set enrichment analysis (GSEA) is an ubiquitously used tool for evaluating pathway enrichment in transcriptional data. Typical experimental design consists in comparing two conditions with several replicates using a differential gene expression test followed by preranked GSEA performed against a collection of hundreds and thousands of pathways. However, the reference implementation of this method cannot accurately estimate small P-values, which significantly limits its sensitivity due to multiple hypotheses correction procedure.
Here we present FGSEA (Fast Gene Set Enrichment Analysis) method that is able to estimate arbitrarily low GSEA P-values with a high accuracy in a matter of minutes or even seconds. To confirm the accuracy of the method, we also developed an exact algorithm for GSEA P-values calculation for integer gene-level statistics. Using the exact algorithm as a reference we show that FGSEA is able to routinely estimate P-values up to 10-100 with a small and predictable estimation error. We systematically evaluate FGSEA on a collection of 605 datasets and show that FGSEA recovers much more statistically significant pathways compared to other implementations.
FGSEA is open source and available as an R package in Bioconductor (http://bioconductor.org/packages/fgsea/) and on GitHub (https://github.com/ctlab/fgsea/). | bioinformatics |
Immunoecology of species with alternative reproductive tactics and strategies Alternative reproductive tactics and strategies (ARTS) refer to polymorphic reproductive behaviours in which in addition to the usual two sexes, there are one or more alternative morphs, usually male, that have evolved the ability to circumvent direct intra-sexual competition. Each morph has its own morphological, ecological, developmental, behavioural, life-history, and physiological profile that shifts the balance between reproduction and self-maintenance, one aspect being immunity. Immunoecological work on species with ARTS, which is the topic of this review, is particularly interesting because the alternative morphs make it possible to separate the effects of sex, per se, from other factors that in other species are inextricably linked with sex. We first summarize the evolution, development and maintenance of ARTS. We then review immunoecological hypotheses relevant to species with ARTS, dividing them into physiological, life-history, and ecological hypotheses. In context of these hypotheses, we critically review in detail all immunoecological studies we could find on species with ARTS. Several interesting patterns emerge. Oddly, there is a paucity of studies on insects, despite the many benefits that arise from working with insects: larger sample sizes, simple immune systems, and countless forms of alternative reproductive strategies and tactics. Of all the hypotheses considered, the immunocompetence handicap hypothesis has generated the greatest amount of work, but not necessarily the greatest level of understanding. Unfortunately, it is often used as a general guiding principle rather than a source of explicitly articulated predictions. Other hypotheses are usually considered a posteriori, but it is perhaps time that they take centre stage. Whereas blanket concepts such as "immunocompetence" and "androgens" might useful to develop a rationale, predictions need to be far more explicitly articulated. Integration so far has been a one-way street, with ecologists delving deeper into physiology, seemingly at the cost of ignoring their organisms evolutionary history and ecology. One possible useful framework is to divide ecological and evolutionary factors affecting immunity into those that stimulate the immune system, and those that depress it. Finally, the contributions of genomics to ecology are being increasingly recognized, including in species with ARTS, but we must ensure that evolutionary and ecological hypotheses drive the effort, as there is no grandeur in the strict reductionist view of life. | evolutionary biology |
Frameshifts and wild-type protein sequences are always highly similar because the genetic code and genomes were optimized for frameshift tolerance Frameshift protein sequences encoded by alternative reading frames of coding genes have been considered meaningless, and frameshift mutations have been considered of little importance for the molecular evolution of coding genes and proteins. However, functional frameshifts have been found widely existing. It was puzzling how a frameshift protein kept its structure and functionality while its amino-acid sequence was changed substantially. Here we show that frame similarities between frameshifts and wild types are higher than random similarities and are defined at the genetic code, gene, and genome levels. In the standard genetic code, frameshift codon substitutions are more conservative than random substitutions. The frameshift tolerability of the standard genetic code ranks in the top 2.0-3.5% of alternative genetic codes, showing that the genetic code is nearly optimal for frameshift tolerance. Furthermore, frameshift-resistant codons (codon pairs) appear more frequently than expected in many genes and certain genomes, showing that the frameshift optimality is reflected not only in the genetic code but more importantly, in its allowance of further optimizing the frameshift tolerance of a particular gene or genome, which shed light on the role of frameshift mutations in molecular and genomic evolution. | genetics |
Estimating the timing of multiple admixture events using 3-locus Linkage Disequilibrium Estimating admixture histories is crucial for understanding the genetic diversity we see in present-day populations. Allele frequency or phylogeny-based methods are excellent for inferring the existence of admixture or its proportions. However, to estimate admixture times, spatial information from admixed chromosomes of local ancestry or the decay of admixture linkage disequilibrium (ALD) is used. One popular method, implemented in the programs ALDER and ROLLOFF, uses two-locus ALD to infer the time of a single admixture event, but is only able to estimate the time of the most recent admixture event based on this summary statistic. To address this limitation, we derive analytical expressions for the expected ALD in a three-locus system and provide a new statistical method based on these results that is able to resolve more complicated admixture histories. Using simulations, we evaluate the performance of this method on a range of different admixture histories. As an example, we apply the method to the Colombian and Mexican samples from the 1000 Genomes project. The implementation of our method is available at https://github.com/Genomics-HSE/LaNeta.
Author summaryWe establish a theoretical framework to model 3-locus admixture linkage disequilibrium of an admixed population taking into account the effects of genetic drift, migration and recombination. The theory is used to develop a method for estimating the times of multiple admixtures events. We demonstrate the accuracy of the method on simulated data and we apply it to previously published data from Mexican and Columbian populations to explore the complex history of American populations in the post-Columbian period. | bioinformatics |
Revisiting the effect of red on competition in humans Bright red coloration is a signal of male competitive ability in animal species across a range of taxa, including non-human primates. Does the effect of red on competition extend to humans? A landmark study in evolutionary psychology established such an effect through analysis of data for four combat sports at the 2004 Athens Olympics [1]. Here we show that the results do not replicate in an equivalent, independent dataset for the 2008 Beijing Olympics, and that there is substantial variation in the fraction of wins by red across sports in both years. We uncover a number of shortcomings with the research design, analysis, and interpretation underlying the original results. For example, the variation observed in the data may reflect bias towards wins by one color over the other, linked to specific features of the tournament structure for the sports analysed. Reanalysis of the data to address these shortcomings indicates that there is no evidence for an effect of red on the outcomes of Olympic combat sports. Our results refute past claims based on analysis of this system, challenging the related notion that any effect of red in human competition is an evolved response shaped by sexual selection. | evolutionary biology |
Resolving the Functional Significance of BRCA1 RING Domain Missense Substitutions Part 1Development and calibration of suitably accurate functional assays for BRCA1 RING domain and BRCT domain missense substitutions could dramatically accelerate clinical classification of rare missense substitutions observed in that gene. Leveraging data from 68,000 full sequence tests of BRCA1 and BRCA2, plus data from the limited number of already classified BRCA1 RING domain missense substitutions, we used logistic regression and related techniques to evaluate three BRCA1 RING domain assays. These were recently described high throughput yeast 2-hybrid and E3 ubiquitin ligase assays, plus a newly developed mammalian 2-hybrid assay. While there were concerns about the accuracy of the yeast 2-hybrid assay and the indirect nature of the ubiquitin ligase assay, the mammalian 2-hybrid assay had excellent correlation with existing missense substitution classifications. After calibration, this assay contributed to classification of one newly reported BRCA1 missense substitution. In principal, the mammalian 2-hybrid assay could be converted to a high-throughput format that would likely retain suitable accuracy.
Part 2How does one achieve clinically applicable classification of the vast majority of all possible sequence variants in disease susceptibility genes? BRCA1 is a high-risk susceptibility gene for breast and ovarian cancer. Pathogenic protein truncating variants are scattered across the open reading frame, but all known missense substitutions that are pathogenic because of missense dysfunction are located in either the amino-terminal RING domain or the carboxy-terminal BRCT domain. Heterodimerization of the BRCA1 and BARD1 RING domains is a molecularly defined obligate activity. Hence, we tested every BRCA1 RING domain missense substitution that can be created by a single nucleotide change for heterodimerization with BARD1 in a Mammalian 2-hybrid (M2H) assay. Downstream of the M2H laboratory assay, we addressed three additional challenges: assay calibration, validation thereof, and integration of the calibrated results with other available data such as computational evidence and patient/population observational data to achieve clinically applicable classification. Overall, we found that about 20% of BRCA1 RING domain missense substitutions are pathogenic. Using a Bayesian point system for data integration and variant classification, we achieved clinical classification of about 89% of observed missense substitutions. Moreover, among missense substitutions not present in the human observational data used here, we find an additional 47 with concordant computational and functional assay evidence in favor of pathogenicity; these are particularly likely to be classified as Likely Pathogenic once human observational data become available. | genetics |
Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software BackgroundComputational biology provides widely used and powerful software tools for testing and making inferences about biological data. In the face of rapidly increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We are have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors are indicative of accurate software.
MethodWe have extracted accuracy and speed ranks from independent benchmarks of different bioinformatic software tools, and evaluated whether the speed, author reputation, journal impact, recency and developer efforts are indicative of accuracy.
ResultsWe found that software speed, author reputation, journal impact, number of citations and age are all unreliable predictors of software accuracy. This is unfortunate because citations, author and journal reputation are frequently cited reasons for selecting software tools. However, GitHub-derived records and high version numbers show that the accurate bioinformatic software tools are generally the product of many improvements over time, often from multiple developers.
DiscussionWe also find that the field of bioinformatics has a large excess of slow and inaccurate software tools, and this is consistent across many sub-disciplines. Meanwhile, there are few tools that are middle-of-road in terms of accuracy and speed trade-offs. We hypothesise that a form of publication-bias influences the publication and development of bioinformatic software. In other words, software that is intermediate in terms of both speed and accuracy may be difficult to publish - possibly due to author, editor and reviewer practices. This leaves an unfortunate hole in the literature as the ideal tools may fall into this gap. For example, high accuracy tools are not always useful if years of CPU time are required, while high speed is not useful if the results are also inaccurate. | bioinformatics |
Correcting Chimeric Crosstalk in Single Cell RNA-seq Experiments As part of the process of preparing sequencing libraries that include unique molecular identifiers (UMIs) such as many single cell RNA-seq (scRNA-seq) libraries, a diverse template must be amplified. During amplification, spurious chimeric molecules can be formed between molecules originating in different cells. While several computational and experimental strategies have been suggested to mitigate the impact of chimeric molecules, suitable approaches for scRNA-seq experiments do not exist. We demonstrate that chimeras become increasingly problematic as samples are sequenced deeply and propose both supervised and unsupervised computational solutions. These solutions are validated in the context of a deeply sequenced species mixing experiment, and, orthogonally, using replicate PCR amplifications of the same scRNA-seq library. Our code is publicly available at https://github.com/asncd/schimera. | bioinformatics |
The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation Predicting a multicellular organisms phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. We test three candidate mechanisms for the accumulation of these organic acids. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.
This work updates the first biorXiv version, February 2017, https://doi.org/10.1101/105437, with an expanded description and additional analysis of the same core data sets and the same FMv2 model, summary tables and supporting, follow-on data from three further studies with further collaborators. This biorXiv revision constitutes the second version of this report. | plant biology |
Aperiodic neural activity is a better predictor of schizophrenia than neural oscillations Diagnosis and symptom severity in schizophrenia is associated with irregularities across neural oscillatory frequency bands, including theta, alpha, beta, and gamma. However, electroencephalographic signals consist of both periodic and aperiodic background activity, characterized by the (1/f) slope of the power spectrum. We compared traditional band-limited periodic oscillatory activity to aperiodic activity, in schizophrenia participants and healthy controls, during an attention task. Classification analysis revealed that the change in slope of the power spectrum better predicted group status than traditional oscillatory power. It even outperformed the predictions made using participants own behavioral performance. Additionally, the differences in slope were highly consistent as they were observed across all electrodes. In sum, the aperiodic slope appears to be a more accurate, consistent, and robust metric to differentiate schizophrenic patients from healthy controls.
Significance statementUnderstanding the neurobiological origins of schizophrenia and identifying reliable and consistent biomarkers are of critical importance in improving treatment of that disease. Numerous studies have reported disruptions to neural oscillations in schizophrenia patients. This has, in part, led to schizophrenia being characterized as a disease of disrupted neural coordination, reflected by changes in frequency band power. We report however that changes in aperiodic background noise (i.e., spectral slope) can also predict clinical status. Unlike band-limited power though, the aperiodic slope predicts status better than participants own behavioral performance. Furthermore, it is a consistent predictor across all electrodes. Alterations in aperiodic noise are consistent with well-established inhibitory neuron dysfunctions associated with schizophrenia, allowing for a direct link between noninvasive EEG and chronic, widespread, neurobiological deficits. | neuroscience |
Population Temporal Structure Supplements The Rate Code During Sensorimotor Transformations Sensorimotor transformations are mediated by premotor brain networks where individual neurons represent sensory, cognitive, and movement-related information. Such multiplexing poses a conundrum - how does a decoder know precisely when to initiate a movement if its inputs are active at times when a movement is not desired (e.g., in response to sensory stimulation)? Here, we propose a novel hypothesis: movement is triggered not only by an increase in firing rate, but critically by a reliable temporal pattern in the population response. Laminar recordings in the superior colliculus (SC), a midbrain region that plays an essential role in orienting eye movements, indicate that the temporal structure across neurons is a factor governing movement initiation. Specifically, using a measure that captures the fidelity of the population code - here called temporal stability - we show that the temporal structure fluctuates during the visual response but becomes increasingly stable during the movement command, even when the mean population activity is similar between the two epochs. Analyses of pseudo-populations in SC and cortical frontal eye fields (FEF) corroborated this model. We also used spatiotemporally patterned microstimulation to causally test the contribution of population temporal stability to movement initiation and found that stable stimulation patterns were more likely to evoke a movement, even when other features of the patterns such as mean pulse rates and population state subspaces were matched. Finally, a spiking neuron model was able to discriminate between stable and unstable input patterns, providing a putative biophysical mechanism for decoding temporal structure. These findings offer an alternative perspective on the relationship between movement preparation and generation by situating the correlates of movement initiation in the temporal features of activity in shared neural substrates. They also suggest a need to look beyond the instantaneous rate code at the single neuron or population level and consider the effects of short-term population history on neuronal communication and behaviour.
SummarySensorimotor transformations are mediated by premotor brain networks where individual neurons represent sensory, cognitive, and movement-related information. Such multiplexing poses a conundrum - how does a decoder know precisely when to initiate a movement if its inputs are active at times when a movement is not desired (e.g., in response to sensory stimulation)? Here, we propose a novel hypothesis: movement is triggered not only by an increase in firing rate, but critically by a reliable temporal pattern in the population response. Laminar recordings in the macaque superior colliculus (SC), a midbrain hub of orienting control, and pseudo-population analyses in SC and cortical frontal eye fields (FEF) corroborated this hypothesis. Importantly, we used spatiotemporally patterned microstimulation to causally verify the importance of temporal structure and demonstrate its role in gating movement initiation. We also offer a spiking neuron model with dendritic integration as a putative mechanism to decode this temporal information. These findings offer new insights into the long-standing debate on movement generation and highlight the importance of short-term population history in neuronal communication and behavior. | neuroscience |
Sexual dimorphism and plasticity in wing shape in three Diptera The ability of powered flight in insects facilitated their great evolutionary success allowing them to occupy various ecological niches. Beyond this primary task, wings are often involved in various premating behaviors, such as the generation of courtship songs and the initiation of mating in flight. These specific functions imply special adaptations of wing morphology, as well as sex-specific wing morphologies. Although wing morphology has been extensively studied in Drosophila melanogaster, a comprehensive understa nding of sexual wing shape dimorphisms and developmental plasticity is missing for other Diptera. Therefore, we raised flies of the three Diptera species Drosophila melanogaster, Ceratitis capitata and Musca domestica at different environmental conditions and applied geometric morphometrics to analyze wing shape. Our data showed extensive interspecific differences in wing shape, as well as a clear sexual wing shape dimorphism in all three species. We revealed an impact of different rearing temperatures wing shape in all three species, which was mostly explained by plasticity in wing size in D. melanogaster. Rearing densities had significant effects on allometric wing shape in D. melanogaster, while no obvious effects were observed for the other two species. Additionally, we do not find evidence for sex-specific response to different rearing conditions in all three species. We determined species-specific and common trends in shape alterations, and we hypothesize developmental and functional implications of our data.
Contribution to the Field StatementThe size and shape of organisms and organs must be tightly controlled during development to ensure proper functionality. However, morphological traits vary considerably in nature contributing to phenotypic diversity. Such variation can be the result of evolutionary adaptations as well as plasticity for example as reaction to changing environmental conditions during development. It is therefore a major aim in Biology to unravel the processes that control differences in adult morphology. Insect wings are excellent models to study how organ size and shape evolves because they facilitate basic tasks such as mating and feeding. Accordingly, a tremendous variety of wings sizes and shapes evolved in nature. Additionally, plasticity in wing morphology in response to different rearing conditions has been observed in many insects contributing to phenotypic diversity. In this work we applied Geometric Morphometrics to study wing shape in the three Diptera species: the Mediterranean fruit fly Ceratitis capitata, the Vinegar fly Drosophila melanogaster and the housefly Musca domestica. Flies were raised in different temperature and density regimes that allowed us to study the effects of these environmental factors on wing shape. Additionally, in accordance with different mating behaviors of these flies, we observed a clear sexual shape dimorphism in all three species. Since the three studied species represent serious pests and disease vectors, our findings may contribute to existing and future monitoring efforts. | zoology |
Laser-free super-resolution microscopy We report that high-density single-molecule super-resolution microscopy can be achieved with a conventional epifluorescence microscope setup and a Mercury arc lamp. The configuration termed as laser-free super-resolution microscopy (LFSM), is an extension of single molecule localisation microscopy (SMLM) techniques and allows single molecules to be switched on and off (a phenomenon termed as "blinking"), detected and localised. The use of a short burst of deep blue excitation (350-380 nm) can be further used to reactivate the blinking, once the blinking process has slowed or stopped. A resolution of 90 nm is achieved on test specimens (mouse and amphibian meiotic chromosomes). Finally, we demonstrate that STED and LFSM can be performed on the same biological sample using a simple commercial mounting medium. It is hoped that this type of correlative imaging will provide a basis for a further enhanced resolution. | biophysics |
The Effects of Central Nervous System Stimulants on Drosophila melanogaster Reproduction Stimulant drugs are used everyday by people around the world. The effect stimulants have on developing human fetuses is widely unknown. The fruit fly Drosophila melanogaster has become a valuable system to model the complex effects and properties of drugs in mammals. In this study, Drosophila is used to analyze the effects of stimulant exposure on reproduction to determine if stimulants cause a significant decrease in the number of offspring produced by parent generations. Caffeine, nicotine, and pseudoephedrine hydrochloride were found to significantly decrease the number of offspring in experimental populations. Further experimentation is necessary to understand the mechanisms underlying these results. | developmental biology |
Proteins with prion-like domains can form viscoelastic condensates that enable membrane remodeling and endocytosis Membrane invagination and vesicle formation are key steps in endocytosis and cellular trafficking. Here, we show that endocytic coat proteins with prion-like domains (PLDs) form hemispherical puncta in the budding yeast, S. cerevisiae. These puncta have the hallmarks of biomolecular condensates and enable membrane remodeling to drive actin-independent endocytosis. The puncta, which we refer to as endocytic condensates, form and dissolve reversibly in response to changes in temperature and solution conditions. The condensates are organized around dynamic protein-protein interaction networks, which involve interactions among PLDs with high glutamine contents. The endocytic coat protein Sla1 is at the hub of the protein-protein interaction network. Using active rheology, we indirectly characterized the material properties of endocytic condensates. These experiments show that endocytic condensates are viscoelastic materials and allow us to estimate the interfacial tension between endocytic condensates and their surroundings. We then adapt the physics of contact mechanics, specifically the contact theory of Hertz, to develop a quantitative framework for describing how interfacial tensions among condensates, the membrane, and the cytosol can deform the plasma membrane to enable actin independent endocytosis. | cell biology |
Intestine-to-neuronal signaling alters risk-taking behaviors in food-deprived Caenorhabditis elegans Animals integrate changes in external and internal environments to generate behavior. While neural circuits detecting external cues have been mapped, less is known about how internal states like hunger are integrated into behavioral outputs. We use the nematode C. elegans to decode how changes in internal nutritional status affects chemosensory behaviors. We show that acute food deprivation leads to a reversible decline in repellent, but not attractant, sensitivity. This behavioral change requires two conserved transcription factors MML-1 (Mondo A) and HLH-30 (TFEB), both of which translocate from the intestinal nuclei to the cytoplasm upon food deprivation. Next, we identify insulin-like peptides INS-23 and INS-31 as candidate ligands relaying food-status signals from the intestine to other tissues. Furthermore, we show that ASI chemosensory neurons use the DAF-2 insulin receptor, PI-3 Kinase, and the mTOR complex to integrate these intestine-released peptides. Together, our study shows how internal food status signals are integrated by transcription factors and intestine-neuron signaling to generate flexible behaviors.
Author SummaryWe have all experienced behavioral changes when we are hungry - the pang in our stomach can cause us to behave erratically. In particular, hungry animals, including humans, are known to pursue behaviors that involve higher risk compared to when they are well-fed. Here we explore the molecular details of this behavior in the invertebrate animal model C. elegans. This behavior, termed sensory integration, shows that C. elegans display reduced copper sensitivity when hungry. Copper is toxic and repellant to C. elegans; reduced avoidance indicates that these animals use riskier food search behaviors when they are hungry. Luckily, like us, this behavioral change is reversible upon re-feeding. This hunger-induced behavioral change is not due to increased attraction to food or depletion of fat stores, but rather insulin signaling between the intestine and specific neurons. We use genetic tools, microscopy, and behavioral tests to determine that this risky behavior involves sensation of "lack of food" in the intestine, release of signaling molecules, and engagement with sensory neurons. Our work highlights new and potentially evolutionarily conserved ways in which intestinal cells and neurons communicate leading to largescale behavioral change, providing further support for the importance of the gut-brain-axis. | neuroscience |
Distinct C4 Sub-Types and C3 Bundle Sheath Isolation In The Paniceae Grasses In C4 plants, the enzymatic machinery underpinning photosynthesis can vary, with, for example, three distinct C4 acid decarboxylases being used to release CO2 in the vicinity of RuBisCO. For decades, these decarboxylases have been used to classify C4 species into three biochemical sub-types. However, more recently the notion that C4 species mix and match C4 acid decarboxylases has increased in popularity and, as a consequence, the validity of specific biochemical sub-types has been questioned. Using five species from the grass tribe Paniceae, we show that, while in some species transcripts encoding multiple C4 acid decarboxylases accumulate, in others, transcript abundance and enzyme activity is almost entirely from one decarboxylase. In addition, the development of a bundle sheath isolation procedure for a close C3 species in the Paniceae enables the preliminary exploration of C4 sub-type evolution. | plant biology |
The effects of an 8-week mindful eating intervention on anticipatory reward responses in striatum and midbrain Obesity is a highly prevalent disease, usually resulting from chronic overeating. Accumulating evidence suggests that increased neural responses during the anticipation of high-calorie food play an important role in overeating. A promising method for counteracting enhanced food anticipation in overeating might be mindfulness-based interventions (MBIs). However, the neural mechanisms by which MBIs can affect food reward anticipation are unclear. In this randomized, actively controlled study, the primary objective was to investigate the effect of an 8-week mindful eating intervention on reward anticipation. On the neural level, we hypothesized that mindful eating would decrease striatal reward anticipation responses. Additionally, responses in the midbrain - from which the reward pathways originate - were explored. Using functional magnetic resonance imaging (fMRI), we tested 58 healthy participants with a wide body mass index range (BMI: 19-35 kg/m2), motivated to change their eating behavior. During scanning they performed an incentive delay task, measuring neural reward anticipation responses to caloric and monetary cues before and after 8 weeks of mindful eating or educational cooking (active control). Compared with the educational cooking intervention, mindful eating affected neural reward anticipation responses, with relatively reduced caloric versus monetary reward responses. This effect was, however, not seen in the striatum, but only in the midbrain. The secondary objective was to assess temporary and long-lasting (one year follow-up) intervention effects on self-reported eating behavior and anthropometric measures (BMI, waist circumference, waist-to-hip-ratio (WHR)). We did not observe effects of the mindful eating intervention on eating behavior. Instead, the control intervention showed temporary beneficial effects on BMI, waist circumference, and diet quality, but not on WHR or self-reported eating behavior, as well as long-lasting increases in knowledge about healthy eating. These results suggest that an 8-week mindful eating intervention may have decreased the relative salience of food cues by affecting midbrain but not striatal reward responses. However, these exploratory results should be verified in confirmatory research.
The primary and secondary objectives of the study were registered in the Dutch Trial Register (NTR): NL4923 (NTR5025). | neuroscience |
Bromodomains regulate dynamic targeting of the PBAF chromatin remodeling complex to chromatin hubs Transcriptional bursting involves genes rapidly switching between active and inactive states. Chromatin remodelers actively target arrays of acetylated nucleosomes at select enhancers and promoters to facilitate or shut down the repeated recruitment of RNA Pol II during transcriptional bursting. It is unknown how acetylated chromatin is dynamically targeted and regulated by chromatin remodelers such as PBAF. Thus, we sought to understand how PBAF targets acetylated chromatin using live-cell single molecule fluorescence microscopy. Our work reveals chromatin hubs throughout the nucleus where PBAF rapidly cycles on and off the genome. Deletion of PBAFs bromodomains impairs targeting, stable engagement and persistent binding on chromatin in hubs. Interestingly, PBAF has a higher probability to stably engage chromatin inside hubs indicating that hubs contain a unique nucleosomal scaffold compared to global chromatin. Dual color imaging of PBAF in hubs near H3.3 or HP1 reveals that PBAF targets both euchromatic and heterochromatic regions with distinct genome binding kinetics that mimic chromatin stability. Removal of PBAFs bromodomains stabilizes H3.3 and HP1 binding within chromatin indicating that bromodomains may play a direct role in remodeling of the nucleosome. Our data, suggests that PBAF differentially and dynamically engages a variety of chromatin structures involved in both activation and repression of transcription via bromodomains. Furthermore, PBAFs binding stability on chromatin may reflect the chromatin remodeling potential of different bound chromatin states.
Statement of SignificanceTranscriptional bursting involves a gene rapidly switching between transcriptionally active and inactive states. To regulate transcriptional bursting, chromatin must interchange between euchromatin and heterochromatin to permit or restrict access of transcription factors including RNA Polymerase II to enhancer and gene promoters. However, little is known regarding how chromatin remodelers dynamically read a rapidly changing 4D epigenome. We used live-cell single molecule imaging to characterize the spatiotemporal chromatin binding dynamics of PBAF, a chromatin remodeler that accesses both euchromatin and heterochromatin to regulate transcription. PBAF cycles on and off chromatin hubs in select nuclear regions where it distinctly engages euchromatin and heterochromatin via bromodomains in its BAF180 subunit. Our study provides the framework to understand how the 4D epigenome is regulated. | cell biology |
cytoNet: Spatiotemporal Network Analysis of Cell Communities We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNets capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin 4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.
Availability and ImplementationQutubLab.org/how | cytoNet contact: [email protected] Brain Initiative Alliance Toolmaker cytoNet site: https://www.braininitiative.org/toolmakers/resources/cytonet/
Author / Lay SummarycytoNet provides an online tool to rapidly characterize relationships between objects within images and video frames. To study complex tissue, cell and subcellular topologies, cytoNet integrates vision science with the mathematical technique of graph theory. This allows the method to simultaneously identify environmental effects on single cells and on network topology. cytoNet has versatile use across neuroscience, stem cell biology and regenerative medicine. cytoNet applications described in this study include: (1) characterizing how sensing pain alters neural circuit activity, (2) quantifying how vascular cells respond to neurotrophic stimuli overexpressed in the brain after injury or exercise, (3) delineating features of fat tissue that may confer resistance to obesity and (4) uncovering structure-function relationships of human stem cells as they transform into neurons. | bioengineering |
Plant genetic effects on microbial hubs impact fitness across field trials Although complex interactions between hosts and microbial associates are increasingly well documented, we still know little about how and why hosts shape microbial communities in nature. In addition, host genetic effects on microbial communities vary widely depending on the environment, obscuring conclusions about which microbes are impacted and which plant functions are important. We characterized the leaf microbiota of 200 A. thaliana genotypes in eight field experiments and detected consistent host effects on specific, broadly distributed microbial OTUs. Host genetics disproportionately influenced hubs within the microbial communities, with their impact then percolating through the community, as evidenced by a decline in the heritability of particular OTUs with their distance to the nearest hub. By simultaneously measuring host performance, we found that host genetics associated with microbial hubs explained over 10% of the variation in lifetime seed production among host genotypes across sites and years. We successfully cultured one of these microbial hubs and demonstrated its growth-promoting effects on plants grown in sterile conditions. Finally, genome-wide association mapping identified many putatively causal genes with small effects on the relative abundance of microbial hubs across sites and years, and these genes were enriched for those involved in the synthesis of specialized metabolites, auxins and the immune system. Using untargeted metabolomics, we corroborate the consistent association of variation in specialized metabolites and microbial hubs across field sites. Together, our results reveal that host natural variation impacts the microbial communities in consistent ways across environments and that these effects contribute to fitness variation among host genotypes. | plant biology |
MARS-Net: Deep learning-based segmentation pipeline for profiling cellular morphodynamics from multiple types of live cell microscopy Quantitative studies of cellular morphodynamics rely on extracting leading-edge velocity time-series based on accurate cell segmentation from live cell imaging. However, live cell imaging has numerous challenging issues about accurate edge localization. Here, we develop a deep learning-based pipeline, termed MARS-Net (Multiple-microscopy- type-based Accurate and Robust Segmentation Network), that utilizes transfer learning and the datasets from multiple types of microscopy to localize cell edges with high accuracy, allowing quantitative profiling of cellular morphodynamics. For effective training with the datasets from multiple types of live cell microscopy, we integrated the pretrained VGG-19 encoder with U-Net decoder and added dropout layers. Using this structure, we were able to train one neural network model that can accurately segment various live cell movies from phase contrast, spinning disk confocal, and total internal reflection fluorescence microscopes. Intriguingly, MARS-Net produced more accurate edge localization than the neural network models trained with single microscopy type datasets, whereas the standard U-Net could not increase the overall accuracy. We expect that MARS-Net can accelerate the studies of cellular morphodynamics by providing accurate segmentation of challenging live cell images. | bioinformatics |
Histone deacetylase inhibition reduces deleterious cytokine release induced by ingenol stimulation IntroductionLatency reversal agents (LRAs), such as protein kinase C (PKC) agonists, constitute a promising strategy for exposing and eliminating the HIV-1 latent reservoir. PKC agonists activate NF-{kappa}B and, in turn, induce deleterious pro-inflammatory cytokine production. Adjuvant pharmacological agents, such as ruxolitinib, a JAK inhibitor, and rapamycin, an mTOR inhibitor, have previously been combined with LRAs to reduce deleterious pro-inflammatory cytokine secretion without inhibiting HIV-1 viral reactivation in vitro. Histone deacetylase inhibitors (HDACi) are known to dampen pro-inflammatory cytokine secretion in the context of other diseases and can synergize with other LRAs to bring dormant proviruses out of latency. In this study we investigated whether a broad panel of epigenetic modifiers, including HDACi, could effectively dampen PKC-induced pro-inflammatory cytokine secretion during latency reversal.
MethodsWe screened an epigenetic modifier library to identify compounds that reduced intracellular IL-6 production induced by the PKC agonist Ingenol-3,20-dibenzoate. We further tested the most promising epigenetic inhibitor class, HDACi, for their ability to reduce a broad panel of pro-inflammatory cytokines and reactivate latent HIV-1 ex vivo.
ResultsWe identified nine epigenetic modulators that reduced PKC-induced intracellular IL-6. In cells from aviremic individuals living with HIV-1, the HDAC1-3 inhibitor, suberohydroxamic acid (SBHA), reduced secretion of pro-inflammatory cytokines TNF-, IL-5, IL-2r, and IL-17 but did not significantly reactivate latent HIV-1 when used in combination with Ingenol-3,20-dibenzoate.
ConclusionThe addition of SBHA to Ingenol-3,20-dibenzoate reduces deleterious cytokine production during latency reversal but does not induce significant viral reactivation in aviremic donor PBMCs. The ability of SBHA to reduce PKC-induced pro-inflammatory cytokines when used in combination with Ingenol-3,20-dibenzoate suggests that SBHA can be used to reduced PKC induced pro-inflammatory cytokines but not to achieve latency reversal in the context of HIV-1. | microbiology |
Plasma amyloid β levels are driven by genetic variants near APOE, BACE1, APP, PSEN2: A genome-wide association study in over 12,000 non-demented participants INTRODUCTIONThere is increasing interest in plasma A{beta} as an endophenotype and biomarker of Alzheimers disease (AD). Identifying the genetic determinants of plasma A{beta} levels may elucidate important processes that determine plasma A{beta} measures.
METHODSWe included 12,369 non-demented participants derived from eight population-based studies. Imputed genetic data and plasma A{beta}1-40, A{beta}1-42 levels and A{beta}1-42/A{beta}1-40 ratio were used to perform genome-wide association studies, gene-based and pathway analyses. Significant variants and genes were followed-up for the association with PET A{beta} deposition and AD risk.
RESULTSSingle-variant analysis identified associations across APOE for A{beta}1-42 and A{beta}1-42/A{beta}1-40 ratio, and BACE1 for A{beta}1-40. Gene-based analysis of A{beta}1-40 additionally identified associations for APP, PSEN2, CCK and ZNF397. There was suggestive interaction between a BACE1 variant and APOE{varepsilon}4 on brain A{beta} deposition.
DISCUSSIONIdentification of variants near/in known major A{beta}-processing genes strengthens the relevance of plasma-A{beta} levels both as an endophenotype and a biomarker of AD. | genetics |
Measuring nonapoptotic caspase activity with a transgenic reporter in mice The protease caspase-3 is a key mediator of apoptotic programmed cell death. But weak or transient caspase activity can contribute to neuronal differentiation, axonal pathfinding, and synaptic long-term depression. Despite the importance of sublethal, or nonapoptotic, caspase activity in neurodevelopment and neural plasticity, there has been no simple method for mapping and quantifying nonapoptotic caspase activity in rodent brains. We therefore generated a transgenic mouse expressing a highly sensitive and specific fluorescent reporter of caspase activity, with peak signal localized to the nucleus. As a proof of concept, we first obtained evidence that nonapoptotic caspase activity influences neurophysiology in an amygdalar circuit. Then focusing on the amygdala, we were able to quantify a sex-specific persistent elevation in caspase activity in females after restraint stress. This simple in vivo caspase activity reporter will facilitate systems-level studies of apoptotic and nonapoptotic phenomena in behavioral and pathological models.
Significance StatementCaspase-3 is an enzyme that can cause cell death when highly active but can also perform important cellular functions, such as maturation and structural changes, when only weakly or transiently active. Despite the importance of this nonlethal type of caspase activity, there is no straightforward method to measure it in live rodents. We therefore developed mice that have a fluorescent reporter that is sensitive enough to detect nonlethal caspase activity. Surprisingly, we found that weak caspase activity influences the synchrony of neuronal firing across different brain regions. We also observed increased caspase activity in female mice after severe stress. This simple, live-animal caspase activity reporter can subserve multiple applications in behavior and pathology research. | neuroscience |
Improved management facilitates return of an iconic fish species Species declines and losses of biota are often associated with shifting baselines in perceived historical abundances, and/or neglect or abandonment of recovery actions aimed at ecological restoration. Such declines are frequently accompanied by contractions in the geographical distribution of the species, with associated negative ecological impacts and diminishing socio-economic benefits. Here we show using citizen science and other data that after 50-60 years of near total absence, the iconic top predator and highly migratory species bluefin tuna, Thunnus thynnus, returned by the hundreds if not thousands in waters near Denmark, Norway and Sweden during August-October 2015-2017. The re-utilisation of this former habitat is part of a geographically more widespread expansion of the summer foraging area to the northern part of the northeast Atlantic Ocean, encompassing waters from east Greenland to west Sweden. The remarkable return to the Skagerrak, Kattegat and North Sea has been facilitated by improved fishery management for bluefin tuna and its prey. Bluefin tuna biomass in the northeast Atlantic and Mediterranean has been increasing since a recovery plan was implemented in the late 2000s, and biomasses of two key prey species (herring, Clupea harengus; mackerel, Scomber scombrus) recovered during the late 1980s-1990s. The reappearance of bluefin tuna in the Skagerrak-Kattegat and other waters of northern Europe, despite a recent history of mismanagement and illegal fishing in the northeast Atlantic and Mediterranean which led to a critical population decline, offers hope that other marine ecological recoveries are possible under improved management of fisheries and ecosystems.
One Sentence SummaryImproved management promotes the return of an ocean icon to northern Europe.
Significance StatementCommercial fisheries are often perceived being in a state of decline and collapse, putting food and economic security at risk. Such declines are frequently accompanied by contractions in stock distribution, negative ecological impacts and diminishing socio-economic benefits. Here we present an example based on one of the worlds most valuable and iconic fish species, bluefin tuna, which demonstrates that effective management of both bluefin tuna and its prey has been a key factor leading to a remarkable reoccupation of formerly lost habitat. This reappearance, following decades of absence, occurred despite the bluefin tuna stock having had a recent, long history of unsustainable and illegal exploitation. Marine ecological recovery actions can be successful, even in situations which may initially appear intractable. | ecology |
Early urinary candidate biomarkers and clinical outcomes of intervention in a rat model of experimental autoimmune encephalomyelitis Multiple sclerosis is a chronic autoimmune demyelinating disease of the central nervous system and is difficult to diagnose in early stages. Without homeostatic control, urine was reported to have the ability to accumulate early changes in the body. We expect that urinary proteome can reflect early changes in the nervous system. In this study, the early urinary proteome changes in a most employed multiple sclerosis rat model (experimental autoimmune encephalomyelitis (EAE)) were analyzed to explore early urinary candidate biomarkers, and early treatment of methylprednisolone were used to evaluate the therapeutic effect. Compare with controls, twenty-five urinary proteins were altered at day 7 when there were no clinical symptoms and no obvious histological changes. Among them, twenty-three have human homologs and fourteen were reported to be differently expressed in the serum/cerebrospinal fluid/brain tissues of multiple sclerosis patients or animal models. Functional analysis showed that the dysregulated proteins were associated with asparagine degradation, neuroinflammation and lipid metabolism. After the early treatment of methylprednisolone, the incidence of encephalomyelitis in the intervention group was only 1/13. This study demonstrates that urine may be a good source of biomarkers for the early detection of multiple sclerosis and early treatment can significantly delay disease progression. These findings may provide important information for early diagnosis and intervention of multiple sclerosis in the future. | biochemistry |
Majority of choice-related variability in perceptual decisions is present in early sensory cortex While performing challenging perceptual tasks such as detecting a barely visible target, our perceptual reports vary across presentations of identical stimuli. This perceptual variability is presumably caused by neural variability in our brains. How much of the neural variability that correlates with the perceptual variability is present in the primary visual cortex (V1), the first cortical processing stage of visual information? To address this question, we recorded neural population responses from V1 using voltage-sensitive dye imaging while monkeys performed a challenging reaction-time visual detection task. We found that V1 population responses in the period leading to the decision correspond more closely to the monkeys report than to the visual stimulus. These results, together with a simple computational model that allows one to quantify the captured choice-related variability, suggest that most of this variability is present in V1 as additive noise, and that areas downstream to V1 contain relatively little independent choice-related variability. | neuroscience |
Removing unwanted variation between samples in Hi-C experiments Hi-C data is commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation changes across the contact map. We present BNBC, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a QTL analysis as well as differential enrichment across cell types. | genomics |
A bacterial GW-effector directly targets Arabidopsis Argonaute 1 to suppress PAMP-triggered immunity and cause disease Pseudomonas syringae (P. syringae) type-III effectors were previously found to suppress the Arabidopsis microRNA (miRNA) pathway through unknown mechanisms. Here, we first show that the P. syringae HopT1-1 effector promotes pathogenicity by suppressing the Arabidopsis Argonaute 1 (AGO1)-dependent miRNA pathway. We further demonstrate that HopT1-1 physically interacts with Arabidopsis AGO1 through conserved glycine/tryptophan (GW) motifs. Importantly, this AGO-binding platform was found to be essential for the ability of HopT1-1 to suppress both miRNA activity and PAMP-Triggered Immunity (PTI). These results therefore indicate that the RNA silencing suppression activity of HopT1-1 is intimately coupled to its virulence function. Overall, these findings provide the first evidence that a bacterial effector has evolved to directly target an AGO protein to suppress PTI and cause disease. | plant biology |
Differential and defective expression of Koala Retrovirus indicate complexity of host and virus evolution Koala retrovirus (KoRV) is unique amongst endogenous (inherited) retroviruses in that its incorporation to the host genome is still active, providing an opportunity to study what drives this fundamental process in vertebrate genome evolution. Animals in the southern part of the natural range of koalas were previously thought to be either virus free or to have only exogenous variants of KoRV with low rates of KoRV induced disease. In contrast, animals in the northern part of their range universally have both endogenous and exogenous KoRV with very high rates of KoRV induced disease such as lymphoma. This paper uses a combination of sequencing technologies, Illumina RNA sequencing of "southern" (south Australian) and "northern" (SE QLD) koalas and CRISPR enrichment and nanopore sequencing of DNA of "southern" (South Australian and Victorian animals) to retrieve full length loci and intregration sites of KoRV variants. We demonstrate that koalas that tested negative to the KoRV pol gene qPCR, used to detect replication competent KoRV, are not in fact KoRV free but harbour defective, presumably endogenous, "RecKoRV" variants that are not fixed between animals. This indicates that these populations have historically been exposed to KoRV and raises questions as to whether these variants have arisen by chance or whether they provide a protective effect from the infectious forms of KoRV. This latter explanation would offer the intriguing prospect of being able to monitor and selectively breed for disease resistance to protect the wild koala population from KoRV induced disease. | microbiology |
Experimental evidence of non-classical brain functions Exploring unknown quantum systems is an experimental challenge. Recent proposals exploring quantum gravity have suggested circumventing this problem by considering the unknown system as a mediator between two known systems. If such a mediation can locally generate entanglement in the known systems, then the mediator must be non-classical.
The same approach may be applicable to other systems, in particular the brain, where speculations about quantum operations in consciousness and cognition have a long history. Translated to the brain, the mediator is then an unknown brain function. For the quantum systems, we could use proton spins of bulk water, which most likely interfere with the any brain function. Entanglement in these spins can be witnessed with multiple quantum coherence (MQC). We based our witness protocol on zero quantum coherence (ZQC) whereby potential signals from local properties were minimised.
For short repetitive periods, we found ZQC signals in large parts of the brain, whereby the temporal appearance resembled heartbeat-evoked potentials (HEPs). Similar to HEPs, we also found that the ZQC signal depended on conscious awareness. Consciousness-related signals have, to our knowledge, not yet been reported in NMR. Remarkably, we could exclude local properties as contrast mechanism because (a) the ZQC signals had no correlates known in conventional MRI, and (b) the ZQC signals only appeared if the local properties of the magnetisation, which are complementary to non-local properties, were reduced. Our findings suggest that we may have witnessed entanglement mediated by consciousness-related brain functions. Those brain functions must then operate non-classically, which would mean that consciousness is non-classical. | bioinformatics |
A GenoChemetic strategy for derivatization of the violacein natural product scaffold Natural products and their analogues are often challenging to synthesise due to their complex scaffolds and embedded functional groups. Solely relying on engineering the biosynthesis of natural products may lead to limited compound diversity. Integrating synthetic biology with synthetic chemistry allows rapid access to much more diverse portfolios of xenobiotic compounds which may accelerate the discovery of new therapeutics. As a proof-of-concept, by supplementing an Escherichia coli strain expressing the violacein biosynthesis pathway with 5-bromo-tryptophan in vitro or tryptophan 7-halogenase RebH in vivo, 6 halogenated analogues of violacein or deoxyviolacein were generated, demonstrating promiscuity of the violacein biosynthesis pathway. Furthermore, 20 new derivatives were generated from 5-brominated violacein analogues via Suzuki-Miyaura cross-coupling reaction directly using the crude extract without prior purification. Herein, we demonstrate a flexible and rapid approach to access diverse chemical space that can be applied to a wide range of natural product scaffolds. | synthetic biology |
Proof of concept continuous event logging in living cells Cells must detect and respond to molecular events such as the presence or absence of specific small molecules. To accomplish this, cells have evolved methods to measure the presence and concentration of these small molecules in their environment and enact changes in gene expression or behavior. However, cells dont usually change their DNA in response to such outside stimuli. In this work, we have engineered a genetic circuit that can enact specific and controlled genetic changes in response to changing small molecule concentrations. Known DNA sequences can be repeatedly integrated into a genomic array such that their identity and order encodes information about past small molecule concentrations that the cell has experienced. To accomplish this, we use catalytically inactive CRISPR-Cas9 (dCas9) to bind to and block attachment sites for the integrase Bxb1. Therefore, through the co-expression of dCas9 and guide RNA, Bxb1 can be directed to integrate one of two engineered plasmids, which correspond to two orthogonal small molecule inducers that can be recorded with this system. We identified the optimal location of guide RNA binding to the Bxb1 attP integrase attachment site, and characterized the detection limits of the system by measuring the minimal small molecule concentration and shortest induction time necessary to produce measurable differences in array composition as read out by Oxford Nanopore long read sequencing technology. | synthetic biology |
Modeling Dynamic Transcriptional Circuits with CRISPRi Targeted transcriptional repression with catalytically inactive Cas9 (CRISPRi) promises to reproduce the functions of traditional synthetic transcriptional circuits, but with better orthogonality, programmability, and extensibility. However, CRISPRi lacks obvious cooperativity-a feature classically considered critical for several classic gene regulatory circuits. We use a simple dynamical model of CRISPRi to show that it can be used to build repressilators, toggle switches, and incoherent feed-forward loops. We also show that the function some of these circuits are expected to be sensitive to several key parameters, and we provide specifications for those parameters. Our modeling reveals key engineering requirements and considerations for the construction of dynamic CRISPRi circuits, and provides a roadmap for building those circuits. | synthetic biology |
Scanning along a compressed timeline of the future Several authors have suggested a deep symmetry between the psychological processes that underlie our ability to remember the past and make predictions about the future. The judgment of recency (JOR) task measures temporal order judgments for the past by presenting pairs of probe stimuli; participants choose the probe that was presented more recently. We performed a short-term relative JOR task and introduced a novel judgment of imminence (JOI) task to study temporal order judgments for the future. In the JOR task, participants were presented with a sequence of stimuli and asked to choose which of two probe stimuli was presented closer to the present. In the JOI task, participants were trained on a probabilistic sequence. After training, the sequence was interrupted with probe stimuli. Participants were asked to choose which of two probe stimuli was expected to be presented closer to the present. Replicating prior work on JOR, we found that RT results supported a backward self-terminating search model operating on a temporally-organized representation of the past. We also showed that RT distributions are consistent with this model and that the temporally-organized representation is compressed. Critically, results for the JOI task probing expectations of the future were mirror-symmetric to results from memory, suggesting a forward self-terminating search model operating on a temporally-organized representation of the future. | animal behavior and cognition |
Single-cell characterization of step-wise acquisition of carboplatin resistance in ovarian cancer Acquired resistance to carboplatin is a major obstacle to the cure of ovarian cancer, but its molecular underpinnings are still poorly understood and often inconsistent between in vitro modeling studies. Using sequential treatment cycles, multiple clones derived from a single ovarian cancer cell reached similar levels of resistance. The resistant clones showed significant transcriptional heterogeneity, with shared repression of cell cycle processes and induction of IFN response signaling, and subsequent pharmacological inhibition of the JAK/STAT pathway led to a general increase in carboplatin sensitivity. Gene-expression based virtual synchronization of 26,772 single cells from 2 treatment steps and 4 resistant clones was used to evaluate the activity of Hallmark gene sets in proliferative (P) and quiescent (Q) phases. Two behaviors were associated with resistance: 1) broad repression in the P phase observed in all clones in early resistant steps and 2) prevalent induction in Q phase observed in the late treatment step of one clone. Furthermore, the induction of IFN response in P phase or Wnt-signaling in Q phase were observed in distinct resistant clones. These observations suggest a model of resistance hysteresis, where functional alterations of the P and Q phase states affect the dynamics of the successive transitions between drug exposure and recovery, and prompts for a precise monitoring of single-cell states to develop more effective schedules for, or combination of, chemotherapy treatments. | cancer biology |
System drift and speciation Even if a species phenotype does not change over evolutionary time, the underlying mechanism may change, as distinct molecular pathways can realize identical phenotypes. Here we use linear system theory to explore the consequences of this idea, describing how a gene network underlying a conserved phenotype evolves, as the genetic drift of small changes to these molecular pathways cause a population to explore the set of mechanisms with identical phenotypes. To do this, we model an organisms internal state as a linear system of differential equations for which the environment provides input and the phenotype is the output, in which context there exists an exact characterization of the set of all mechanisms that give the same input-output relationship. This characterization implies that selectively neutral directions in genotype space should be common and that the evolutionary exploration of these distinct but equivalent mechanisms can lead to the reproductive incompatibility of independently evolving populations. This evolutionary exploration, or system drift, is expected to proceed at a rate proportional to the amount of intrapopulation genetic variation divided by the effective population size (Ne). At biologically reasonable parameter values this could lead to substantial interpopulation incompatibility, and thus speciation, on a time scale of Ne generations. This model also naturally predicts Haldanes rule, thus providing a concrete explanation of why heterogametic hybrids tend to be disrupted more often than homogametes during the early stages of speciation. | evolutionary biology |
The effectiveness of glass beads for plating cell cultures Cell plating, the spreading out of a liquid suspension of cells on a surface followed by colony growth, is a common laboratory procedure in microbiology. Despite this, the exact impact of its parameters on colony growth has not been extensively studied. A common protocol involves the shaking of glass beads within a petri dish containing solid growth media. We investigated the effects of multiple parameters in this protocol - the number of beads, the shape of movement, and the number of movements. Standard suspensions of Escherichia coli were spread while varying these parameters to assess their impact on colony growth. Results were assessed by a variety of metrics - the number of colonies, the mean distance between closest colonies, and the variability and uniformity of their spatial distribution. Finally, we devised a mathematical model of shifting billiard to explain the heterogeneities in the observed spatial patterns. Exploring the parameters that affect the most fundamental techniques in microbiology allows us to better understand their function, giving us the ability to precisely control their outputs for our exact needs. | biophysics |
Iron oxidation by a fused cytochrome-porin common to diverse iron-oxidizing bacteria Iron (Fe) oxidation is one of Earths major biogeochemical processes, key to weathering, soil formation, water quality, and corrosion. However, our understanding of microbial contribution is limited by incomplete knowledge of microbial iron oxidation mechanisms, particularly in neutrophilic iron-oxidizers. The genomes of many, diverse iron-oxidizers encode a homolog to an outer-membrane cytochrome (Cyc2) shown to oxidize iron in two acidophiles. Phylogenetic analyses show Cyc2 sequences from neutrophiles cluster together, suggesting a common function, though this function has not been verified in these organisms. Therefore, we investigated the iron oxidase function of heterologously expressed Cyc2 from a neutrophilic iron-oxidizer Mariprofundus ferrooxydans PV-1. Cyc2PV-1 is capable of oxidizing iron, and its redox potential is 208 {+/-} 20 mV, consistent with the ability to accept electrons from Fe2+ at neutral pH. These results support the hypothesis that Cyc2 functions as an iron oxidase in neutrophilic iron-oxidizing organisms. Sequence analysis and modeling reveal the entire Cyc2 family share a unique fused cytochrome-porin structure, with a defining consensus motif in the cytochrome region. Based on structural analyses, we predict that the monoheme cytochrome Cyc2 specifically oxidizes dissolved Fe2+, in contrast to multiheme iron oxidases, which may oxidize solid Fe(II). With our results, there is now functional validation for diverse representatives of Cyc2 sequences. We present a comprehensive Cyc2 phylogenetic tree and offer a roadmap for identifying cyc2/Cyc2 homologs and interpreting their function. The occurrence of cyc2 in many genomes beyond known iron-oxidizers presents the possibility that microbial iron oxidation may be a widespread metabolism.
ImportanceIron is practically ubiquitous across Earths environments, central to both life and geochemical processes, which depend heavily on the redox state of iron. Although iron oxidation, or "rusting," can occur abiotically at near neutral pH, we find neutrophilic iron-oxidizing bacteria (FeOB) are widespread, including in aquifers, sediments, hydrothermal vents, pipes, and water treatment systems. FeOB produce highly reactive Fe(III) oxyhydroxides that bind a variety of nutrients and toxins, thus these microbes are likely a controlling force in iron and other biogeochemical cycles. There has been mounting evidence that Cyc2 functions as an iron oxidase in neutrophiles, but definitive proof of its function has long eluded us. This work provides conclusive biochemical evidence of iron oxidation by Cyc2 from neutrophiles. Cyc2 is common to a wide variety of iron-oxidizers, including acidophilic and phototrophic iron-oxidizers, suggesting that this fused cytochrome-porin structure is especially well-adapted for iron oxidation. | microbiology |
Novel Integrative Modeling of Molecules and Morphology Pinpoints Caninae Evolution across Timescales Evolutionary models account for either population- or species-level processes, but usually not both. We introduce a new model, the FBD-MSC, which makes it possible for the first time to integrate both the genealogical and fossilization phenomena, by means of the multispecies coalescent (MSC) and the fossilized birth-death (FBD) processes. Using this model, we reconstruct the phylogeny representing all extant and many fossil Caninae, recovering both the relative and absolute time of speciation events. We quantify known inaccuracy issues with divergence time estimates using the popular strategy of concatenating molecular alignments, and show that the FBD-MSC solves them. Our new integrative method and empirical results advance the paradigm and practice of probabilistic total evidence analyses in evolutionary biology. | evolutionary biology |
Dynamic Flux Balance Analysis Models in SBML Computational models in systems biology and systems medicine are typically simulated using a single formalism such as ordinary differential equations (ODE). However, more complex models require the coupling of multiple formalisms since different biological phenomena are better described by different methods. For example, metabolism in steady state is often modeled using flux-balance analysis (FBA) whereas dynamic changes of model components are better described via ODEs. The coupling of FBA and ODE modeling formalisms results in dynamic FBA models. A major challenge is how to describe such hybrid models that couple multiple formalisms in a standardized way so that they can be exchanged between tools and simulated consistently in a reproducible manner. This paper presents a scheme for encoding and implementation of dynamic FBA models in the Systems Biology Markup Language (SBML), thereby enabling the exchange of multi-framework computational models between software tools. We demonstrate the feasibility of the approach using various example models and show that different tools are able to simulate the hybrid models and agree on the results. As part of this work, two independent implementations of a multi-framework simulation method for dynamic FBA have been developed supporting such models: iBioSim and sbmiutils. | bioinformatics |
Seidr: Efficient Calculation of Robust Ensemble Gene Networks Gene regulatory and gene co-expression networks are powerful research tools for identifying biological signal within high-dimensional gene expression data. In recent years, research has focused on addressing shortcomings of these techniques with regard to the low signal-to-noise ratio, non-linear interactions and dataset dependent biases of published methods. Furthermore, it has been shown that aggregating networks from multiple methods provides improved results. Despite this, few usable and scalable software tools have been implemented to perform such best-practice analyses. Here, we present Seidr (stylized Seithr), a software toolkit designed to assist scientists in gene regulatory and gene co-expression network inference. Seidr creates community networks to reduce algorithmic bias and utilizes noise corrected network backboning to prune noisy edges in the networks.
Using benchmarks in real-world conditions across three eukaryotic model organisms, Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana, we show that individual algorithms are biased toward functional evidence for certain gene-gene interactions. We further demonstrate that the community network is less biased, providing robust performance across different standards and comparisons for the model organisms.
Finally, we apply Seidr to a network of drought stress in Norway spruce (Picea abies (L.) H. Krast) as an example application in a non-model species. We demonstrate the use of a network inferred using Seidr for identifying key components, communities and suggesting gene function for non-annotated genes. | bioinformatics |
High-throughput microcolony growth analysis from suboptimal low-magnification micrographs New technological advances have enabled high-throughput phenotyping at the single-cell level, yet analyzing the large amount of data generated by high throughput phenotyping experiments automatically and accurately is a considerable challenge. Here we introduce Processing Images Easily (PIE), software that automatically tracks growth of microbial colonies in low-magnification brightfield images by combining adaptive object-center recognition with gradient-based object-outline recognition. PIE recognizes colony outlines very robustly and accurately across a wide range of image brightnesses, focal depths, and organisms. Beyond accurate colony recognition, PIE is designed to easily integrate with complex experiments, allowing colony tracking across multiple experimental phases and classification based on fluorescence intensity. We show that PIE can be used to accurately measure the growth rates of large numbers (>90,000) of bacterial or yeast microcolonies in a single-time-lapse experiment, allowing calculation of population-wide growth properties. Finally, PIE is able to track individual colonies across multiple experimental phases, measuring both growth and fluorescence properties of the microcolonies.
Author SummaryHigh-throughput microscopy has enabled automated collection of large amounts of growth and gene-expression data in microbes. Computational methods that can precisely recognize and track organisms in images are essential to performing measurements at scale using automated microscopy. We have developed PIE, software that automatically recognizes microbial colonies in microscopy images, tracks them in imaging time-series, and performs measurements of growth and, potentially, gene expression. PIE is highly effective on low-resolution images, outperforming current state-of-the-art approaches in both speed and accuracy, and works well in microbes of varying shapes and sizes. In addition, PIE allows tracking microcolonies across arbitrary sequences of experimental phases, each collecting data in different modalities. We show that PIE allows measurement of growth and fluorescence properties in tens of thousands of microbial colonies in a single experiment, and that in turn the scale of these measurements can lead to important insights about interindividual differences in growth and stress response. PIE is available as a Python package (https://doi.org/10.5281/zenodo.4987127) with documentation currently at https://pie-image.readthedocs.io/; users can also run analysis on individual images or time-series without the need to install PIE by using our web application, currently available at http://pie.hpc.nyu.edu/. | bioinformatics |
Visual and auditory brain areas share a representational structure that supports emotion perception Emotionally expressive music and dance occur together across the world. This may be because features shared across the senses are represented the same way even in different sensory brain areas, putting music and movement in directly comparable terms. These shared representations may arise from a general need to identify environmentally relevant combinations of sensory features, particularly those that communicate emotion. To test the hypothesis that visual and auditory brain areas share a representational structure, we created music and animation stimuli with crossmodally matched features expressing a range of emotions. Participants confirmed that each emotion corresponded to a set of features shared across music and movement. A subset of participants viewed both music and animation during brain scanning, revealing that representations in auditory and visual brain areas were similar to one another. This shared representation captured not only simple stimulus features, but also combinations of features associated with emotion judgments. The posterior superior temporal cortex represented both music and movement using this same structure, suggesting supramodal abstraction of sensory content. Further exploratory analysis revealed that early visual cortex used this shared representational structure even when stimuli were presented auditorily. We propose that crossmodally shared representations support mutually reinforcing dynamics across auditory and visual brain areas, facilitating crossmodal comparison. These shared representations may help explain why emotions are so readily perceived and why some dynamic emotional expressions can generalize across cultural contexts. | neuroscience |
Bayesian model comparison for rare variant association studies Whole genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery and inference that are not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach that we refer to as MRP (Multiple Rare-variants and Phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies. The approach requires only summary statistic data. To demonstrate the efficacy of MRP, we apply our method to exome sequencing data (N = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover previously-verified signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Notable non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, IQGAP2 and mean platelet volume, and JAK2 and platelet count and crit (mass). Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates into four clusters, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes and lipid-related traits. Overall, we show that the MRP model comparison approach is able to improve upon useful features from widely-used meta-analysis approaches for rare variant association analyses and prioritize protective modifiers of disease risk. | genetics |
Nanoscale colocalization of NK cell activating and inhibitory receptors controls signal integration NK cell responses depend on the balance of signals from inhibitory and activating receptors. However, how the integration of antagonistic signals occurs upon NK cell-target cell interaction is not fully understood. Here, we provide evidence that NK cell inhibition via the inhibitory receptor Ly49A is dependent on its relative colocalization at the nanometer scale with the activating receptor NKG2D upon immune synapse (IS) formation. NKG2D and Ly49A signal integration and colocalization was studied using NKG2D-GFP and Ly49A-RFP-expressing primary NK cells, forming ISs with NIH3T3 target cells, with or without expression of single chain trimer (SCT) H2-Dd and an extended form of SCT H2-Dd-CD4 MHC-I molecules. Nanoscale colocalization was assessed by Forster resonance energy transfer (FRET) between NKG2D-GFP and Ly49A-RFP and measured for each synapse. In the presence of their respective cognate ligands, NKG2D and Ly49A colocalize at a nanometer scale leading to NK cell inhibition. However, increasing the size of the Ly49A ligand reduced the nanoscale colocalization with NKG2D consequently impairing Ly49A-mediated inhibition. Thus, our data shows NK cell signal integration is critically dependent on the dimensions of NK cell ligand-receptor pairs by affecting their relative nanometer-scale colocalization at the IS. Together, our results suggest the balance of NK cell signals, and NK cell responses, are determined by the relative nanoscale colocalization of activating and inhibitory receptors in the immune synapse. | immunology |
Genie: An interactive real-time simulation for teaching genetic drift Neutral evolution is a fundamental concept in evolutionary biology but teaching this and other non-adaptive concepts is specially challenging. Here we present Genie, a browser-based educational tool that facilitates demonstration of concepts such as genetic drift, population isolation, gene flow, and genetic mutation. Because it does not need to be downloaded and installed, Genie can scale to large groups of students and is useful for both in-person and online instruction. Genie was used to teach genetic drift to Evolution students at Arizona State University during Spring 2016 and Spring 2017. The effectiveness of Genie to teach key genetic drift concepts and misconceptions was assessed with the Genetic Drift Inventory developed by Price et al. (2014). Overall, Genie performed comparably to that of traditional static methods across all evaluated classes. We have empirically demonstrated that Genie can be successfully integrated with traditional instruction to reduce misconceptions about genetic drift. | scientific communication and education |
The effect of mutational robustness on the evolvability of multicellular organisms Canalization involves mutational robustness, the lack of phenotypic change as a result of genetic mutations. Given the large divergence in phenotype across species, understanding the relationship between high robustness and evolvability has been of interest to both theorists and experimentalists. Although canalization was originally proposed in the context of multicellular organisms, the effect of multicellularity on evolvability has not been considered by theoreticians. We address this issue using a Boolean population model with explicit representation of an environment in which multicellular individuals with explicit genotype and phenotype evolve. Robustness is described by a single real number between zero and one. We find that high robustness is favored in constant environments, and lower robustness is favored after environmental change. Multicellularity severely constrains robustness: peak evolvability occurs at an absolute level of robustness of about 0.99 compared with values of about 0.5 in a classical neutral network model. Multicellularity results in a sharp peak of evolvability in which the maximum is set by the fact that the fixation of adaptive mutations becomes more improbable as robustness decreases. When robustness is put under genetic control, robustness levels leading to maximum evolvability are selected for, but maximal relative fitness appears to require recombination. | evolutionary biology |
The importance of semantic network brain regions in integrating prior knowledge with an ongoing dialogue To understand a dialogue we need to know the specific topics that are being discussed. This enables us to integrate our knowledge of what was said previously, in order to interpret the current dialogue. Here, we selectively manipulated knowledge about the narrative content of dialogues between two people, presented in short videos. The videos were clips taken from television situation comedies and the speech in the first-half of the clip could either be presented normally (high context) or spectrally rotated in order to render it unintelligible (low context). Knowledge of the preceding narrative boosted memory for the following dialogues as well as increased the inter-subject semantic similarity of recalled descriptions of the dialogues. Sharing knowledge of the preceding narrative across participants had two effects on fMRI markers of neural processing: (1) it strengthened temporal inter-subject correlations in regions including the left angular (AG) and inferior frontal gyri (IFG), and (2) it increased spatial inter-subject pattern similarity in the bilateral anterior temporal lobes (ATL). We argue that these brain regions, which are known to be involved in semantic processing, support the activation and integration of prior knowledge, which helps people to better understand and remember dialogues as they unfold. | neuroscience |
Y chromosomal noncoding RNAs regulate autosomal gene expression via piRNAs in mouse testis Majority of the genes expressed during spermatogenesis are autosomal. Mice with different deletions of Yq show sub-fertility, sterility and sperm abnormalities. The connection between Yq deletion and autosomal gene regulation is not well understood. We describe a novel mouse Yq-derived long noncoding RNA, Pirmy, which shows unprecedented number of splice variants in testis. Further, Pirmy transcript variants act as templates for several piRNAs. We identified ten differentially expressed autosome-encoded sperm proteins in mutant mice. Pirmy transcript variants have homology to 5/3UTRs of these deregulated autosomal genes. Thus, subfertility in Y-deleted mice appears to be a polygenic phenomenon that is partially regulated epistatically by the Y-chromosome. Our study provides novel insights into possible role of MSY-derived ncRNAs in male fertility and reproduction. Finally, sperm phenotypes from the Y-deleted mice seem to be similar to that reported in inter-specific male-sterile hybrids. Taken together, this study provides novel insights into possible role of Y-derived ncRNAs in male sterility and speciation. | genomics |
Effects of adaptive harvesting on fishing down processes and resilience changes in predator-prey systems Many world fisheries display a declining mean trophic level of catches. This "fishing down the food web" is often attributed to reduced densities of high-trophic-level species. We show here that the fishing down pattern can actually emerge from the adaptive harvesting of a predator-prey community, where changes in fishing patterns are driven by the relative profitabilities of the harvested species. The shift from a predator- to a prey-focused fishing pattern can yield abrupt changes in the system, strongly impacting species densities. Such regime shifts occur when the predator species is highly valuable relative to the prey, and when the top-down control on the prey is strong. Moreover, we find that when the two species are jointly harvested, high adaptation speeds can reduce the resilience of fisheries. Our results therefore suggest that flexibility in harvesting strategies will not necessarily benefit fisheries but may actually harm their sustainability. | ecology |
Does deterministic coexistence theory matter in a finite world? Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e. non-integer) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature species are composed of discrete individuals subject to demographic stochasticity, and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. Here we test the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically-informed estimates of coexistence times for a natural system. Strikingly, we find that for species expected to deterministically coexist, habitat sizes containing only tens of individuals have predicted coexistence times of greater than 1, 000 years. We also find that invasion growth rates explain 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species equilibrium population sizes could most (> 99%) of the variation in species coexistence times be explained. This integration is achieved with demographically uncoupled single species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species coexistence, while highlighting the need to incorporate information on species equilibrium population sizes in addition to invasion growth rates. | ecology |
Splicing motifs are organized within global structural scaffold of a pre-mRNA The specific recognition of splice signals at or near exon-intron junctions is not explained by their weak conservation and instead is postulated to require a multitude of features embedded in the pre-mRNA strand. We explored the possibility of three-dimensional structural scaffold of AdML - a model pre-mRNA substrate - guiding early spliceosomal components to the splice signal sequences. We find that mutations in the non-cognate splice signal sequences impede recruitment of early spliceosomal components due to disruption of the global structure of the pre-mRNA. We further find that the pre-mRNA segments potentially interacting with the early spliceosomal component U1 snRNP are distributed across the intron, that there is a spatial proximity of 5' and 3' splice sites within the pre-mRNA scaffold, and that an interplay exists between the structural scaffold and splicing regulatory elements in recruiting early spliceosomal components. These results suggest that early spliceosomal components can recognize a three-dimensional structural scaffold beyond the short splice signal sequences, and that in our model pre-mRNA, this scaffold is formed across the intron involving the major splice signals. This provides a conceptual basis to analyze the contribution of recognizable three-dimensional structural scaffolds to the splicing code across the mammalian transcriptome. | biochemistry |
Manipulation of the unfolded protein response: a pharmacological strategy against coronavirus infection Coronavirus infection induces the unfolded protein response (UPR), a cellular signalling pathway composed of three branches, triggered by unfolded proteins in the endoplasmic reticulum (ER) due to high ER load. We have used RNA sequencing and ribosome profiling to investigate holistically the transcriptional and translational response to cellular infection by murine hepatitis virus (MHV), often used as a model for the Betacoronavirus genus to which the recently emerged SARS-CoV-2 also belongs. We found the UPR to be amongst the most significantly up-regulated pathways in response to MHV infection. To confirm and extend these observations, we show experimentally the induction of all three branches of the UPR in both MHV- and SARS-CoV-2-infected cells. Over-expression of the SARS-CoV-2 ORF8 or S proteins alone is itself sufficient to induce the UPR. Remarkably, pharmacological inhibition of the UPR greatly reduced the replication of both MHV and SARS-CoV-2, revealing the importance of this pathway for successful coronavirus replication. This was particularly striking when both IRE1 and ATF6 branches of the UPR were inhibited, reducing SARS-CoV-2 virion release [~]1,000-fold. Together, these data highlight the UPR as a promising antiviral target to combat coronavirus infection.
Author SummarySARS-CoV-2 is the novel coronavirus responsible for the COVID-19 pandemic which has resulted in over 100 million cases since the end of 2019. Most people infected with the virus will experience mild to moderate respiratory illness and recover without any special treatment. However, older people, and those with underlying medical problems like chronic respiratory disease are more likely to develop a serious illness. So far, more than 2 million people have died of COVID-19. Unfortunately, there is no specific medication for this viral disease.
In order to produce viral proteins and to replicate their genetic information, all coronaviruses use a cellular structure known as the endoplasmic reticulum or ER. However, the massive production and modification of viral proteins stresses the ER and this activates a compensatory cellular response that tries to reduce ER protein levels. This is termed the unfolded protein response or UPR. We believe that coronaviruses take advantage of the activation of the UPR to enhance their replication.
The UPR is also activated in some types of cancer and neurodegenerative disorders and UPR inhibitor drugs have been developed to tackle these diseases. In this work, we have tested some of these compounds in human lung cells infected with SARS-CoV-2 and found that virus production was reduced 1000-fold in human lung cells. | microbiology |
Dissecting indirect genetic effects from peers in laboratory mice The phenotype of one individual can be affected not only by the individuals own genotypes (direct genetic effects, DGE) but also by genotypes of interacting partners (indirect genetic effects, IGE). IGE have been detected using polygenic models in multiple species, including laboratory mice and humans. However, the underlying mechanisms remain largely unknown. Genome-wide association studies of IGE (igeGWAS) can point to IGE genes, but have not yet been applied to non-familial IGE arising from "peers" and affecting biomedical phenotypes. In addition, the extent to which igeGWAS will identify loci not identified by dgeGWAS remains an open question. Finally, findings from igeGWAS have not been confirmed by experimental manipulation.
We leveraged a dataset of 170 behavioural, physiological and morphological phenotypes measured in 1,812 genetically heterogeneous laboratory mice to study IGE arising between same-sex, adult, unrelated laboratory mice housed in the same cage. We developed methods for igeGWAS in this context and identified 24 significant IGE loci for 17 phenotypes (FDR < 10%). There was no overlap between IGE loci and DGE loci for the same phenotype, which was consistent with the moderate genetic correlations between DGE and IGE for the same phenotype estimated using polygenic models. Finally, we fine-mapped seven significant IGE loci to individual genes and confirmed, in an experiment with a knockout model, that Epha4 gives rise to IGE on stress-coping strategy and wound healing.
Our results demonstrate the potential for igeGWAS to identify IGE genes and shed some light into the mechanisms of peer influence. | genetics |
Spatial distribution of private gene mutations in clear cell renal cell carcinoma Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction, and might explain clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC. | cancer biology |
DsbA is a redox-switchable mechanical chaperone DsbA is a ubiquitous bacterial oxidoreductase that associates with substrates during and after translocation, yet its involvement in protein folding and translocation remains an open question. Here we demonstrate a redox-controlled chaperone activity of DsbA, on both cysteine-containing and cysteine-free substrate, using a magnetic tweezers-based single molecule force spectroscopy that enables independent measurements of oxidoreductase activity and chaperone behavior. Interestingly we found, this chaperone activity is tuned by the oxidation state of DsbA; oxidized DsbA is a strong promoter of folding, but the effect is weakened by reduction of the catalytic CXXC motif. We further localize the chaperone binding site of DsbA using a seven-residue peptide which effectively blocks the chaperone activity. We calculated that DsbA assisted folding of proteins in the periplasm generates enough mechanical work to decrease the ATP consumption needed for periplasmic translocation by up to 33%. In turn, pharmacologic inhibition of this chaperone activity may open up a new class of anti-virulence agents. | biophysics |
A constraints-based theory of senescence: imbalance of epigenetic and non-epigenetic information in histone crosstalk Cellular aging has been progressively elucidated by science. However, the fundamental cause of senescence--i.e., why organisms age at the multicellular-individual level--remains unclear. A recent theory of individuated multicellularity describes the emergence and growth of crucial information content for cell differentiation. This information is mostly conveyed in the non-epigenetic (i.e., transcription uncorrelated) histone crosstalk near transcription start sites. According to this theory, the non-epigenetic content emerges and grows at the expense of the information capacity for epigenetic content. If this "reassignment" of information capacity continues after adulthood, it may explain the senescence phenomenon. Here, I present a novel, falsifiable theory describing an uninterrupted growth of capacity for non-epigenetic information at the expense of that for epigenetic information not only during ontogeny but also throughout adulthood. As a byproduct, this continuous "reassignment" of capacity effectively creates an information imbalance in histone crosstalk, which in turn overregulates transcriptional levels. This overregulation is to be understood as transcriptional levels becoming more and more accurate but also less and less precise with respect to the needs of the multicellular individual--up to the point of dysfunctionality. This epigenetic/non-epigenetic information imbalance is proposed to be the primary reason why individuated multicellular organisms senesce. | developmental biology |
Cargo-Loading of Misfolded Proteins into Extracellular Vesicles: The CSPα-EV Export Pathway Extracellular vesicles (EVs) are secreted vesicles of diverse size and cargo that are implicated in the cell-to-cell transmission of disease-causing-proteins in several neurodegenerative diseases. Mutant huntingtin, the disease-causing entity in Huntingtons disease, has an expanded polyglutamine track at the N terminus that causes the protein to misfold and form toxic intracellular aggregates. In Huntingtons disease, mutant huntingtin aggregates are transferred between cells by an unknown route. We have previously identified a cellular pathway that is responsible for the export of mutant huntingtin via extracellular vesicles, given the heterogeneity of EVs, here we examine the specific EVs involved. In this work we expressed a form of polyglutamine expanded huntingtin (GFP-tagged 72Qhuntingtinexon1) in cells to assess the EVs involved in cellular export. We demonstrate that the molecular chaperone, cysteine string protein (CSP; DnaJC5), mediates export of disease-causing-polyglutamine-expanded huntingtin cargo via two distinct vesicle populations of 180-240nm and 15-30m. In doing so, our data links the molecular chaperone, CSP, and the packaging of pathogenic misfolded huntingtin into two separate extracellular vesicles pathways. | neuroscience |
Structurally Constrained Effective Brain Connectivity The relationship between structure and function is of interest in many research fields involving the study of complex biological processes. In neuroscience in particular, the fusion of structural and functional data can help understanding the underlying principles of the operational networks in the brain. To address this issue, this paper proposes a constrained autoregressive model leading to a representation of "effective" connectivity that can be used to better understand how the structure modulates the function. Or simply, it can be used to find novel biomarkers characterizing groups of subjects. In practice, an initial structural connectivity representation is re-weighted to explain the functional co-activations. This is obtained by minimizing the reconstruction error of an autoregressive model constrained by the structural connectivity prior. The model has been designed to also include indirect connections, allowing to split direct and indirect components in the functional connectivity, and it can be used with raw and deconvoluted BOLD signal.
The derived representation of dependencies was compared to the well known dynamic causal model, giving results closer to known ground-truth. Further evaluation of the proposed effective network was performed on two typical tasks. In a first experiment the direct functional dependencies were tested on a community detection problem, where the brain was partitioned using the effective networks across multiple subjects. In a second experiment the model was validated in a case-control task, which aimed at differentiating healthy subjects from individuals with autism spectrum disorder. Results showed that using effective connectivity leads to clusters better describing the functional interactions in the community detection task, while maintaining the original structural organization, and obtaining a better discrimination in the case-control classification task.
HighlightsO_LIA method to combine structural and functional connectivity by using autoregressive model is proposed.
C_LIO_LIThe autoregressive model is constrained by structural connectivity defining coefficients for Granger causality.
C_LIO_LIThe usefulness of the generated effective connections is tested on simulations, ground-truth default mode network experiments, a classification and clustering task.
C_LIO_LIThe method can be used for direct and indirect connections, and with raw and deconvoluted BOLD signal.
C_LI | neuroscience |
Characterization of Animal Movement Patterns using Information Theory: a Primer Understanding the movement patterns of animals across different spatio-temporal scales, conditions, habitats and contexts is becoming increasingly important for addressing a series of questions in animal behaviour studies, such as mapping migration routes, evaluating resource use, modelling epidemic spreading in a population, developing strategies for animal conservation as well as understanding several emerging patterns related to feeding, growth and reproduction. In recent times, information theory has been successfully applied in several fields of science, in particular for understanding the dynamics of complex systems and characterizing adaptive social systems, such as dynamics of entities as individuals and as part of groups.
In this paper, we describe a series of non-parametric information-theoretic measures that can be used to derive new insights about animal behaviour with a specific focus on movement patterns, namely Shannon entropy, Mutual information, Kullback-Leibler divergence and Kolmogorov complexity. In particular, we believe that the metrics presented in this paper can be used to formulate new hypotheses that can be verified potentially through a set of different observations and be complementary to existing techniques. We show how these measures can be used to characterize the movement patterns of several animals across different habitats and scales. Specifically, we show the effectiveness in using Shannon entropy to characterize the movement of sheep with Batten disease, mutual information to measure association in pigeons, Kullback-Leibler divergence to study the flights of Turkey vulture, and Kolmogorov complexity to find similarities in the movement patterns of animals across different scales and habitats. Finally, we discuss the limitations of these methods and we outline the challenges in this research area. | ecology |
Sperm morphology differences associated with pig fertility Artificial insemination is routine in commercial pig breeding, and as such, the use of high-quality semen samples is imperative. Here, we have developed a novel, semi-automated, software-based approach to assess pig sperm nucleus morphology in greater detail than was previously possible. This analysis identified subtle morphological differences between samples assessed by the industry as normal and those assessed as abnormal. 50 normal and 50 abnormal samples that were initially categorised using manual assessment to industry standards, were investigated using this new method, with at least 200 fixed stained sperm heads analysed in each case. Differences in sperm nuclear morphology were observed between normal and abnormal samples; specifically, normal samples were associated with higher mean nuclear area, a consequence of a greater head width and a lower variability between sperm heads. This novel, unbiased and fast analysis method demonstrates a significant difference in sperm head morphology between normal and abnormal pig sperm and has the potential to be further developed to be used as a tool for sperm morphology assessment both in the pig breeding industry and potentially in human assisted reproductive technologies. | developmental biology |
Direct programming of human mammary self-organised organoids by miR-106a-3p Organoids development relies on the self-organizing properties of adult stem cells to create structures which recapitulate the architecture, functionality, and genetic signature observed in original tissues. Little is known about of the exact nature of the intrinsic cell properties at the origin of organoid generation, and of the signaling pathways governing their differentiation. Herein, we carried out a functional microRNA screen to identify miRNAs at the origin of organoid generation from human epithelial cell culture. We uncover miR-106a-3p that initiates and promotes organoids. This miRNA acts as a master inducer of the expression of the three core pluripotency transcription factors (NANOG, OCT4 and SOX2) through the regulation of a set of 10 genes, and thus strengthening the reprogramming and cell differentiation of human epithelial cells into organoids. These data demonstrate that organoids can be directly generated from human epithelial cells by only one miRNA: miR-106a-3p. Hence, we appear to have identified a new determinant of organoid identity, which plays a role in reprogramming, cell differentiation and tissue engineering. | cell biology |
Polymer brush bilayers at thermal equilibrium: A density functional theory approach By means of the density functional theory (DFT) framework, the longstanding problem of the polymer brush bilayers at thermal equilibrium is studied. The calculated density profiles reveal that the brushes balance compression and interpenetration when they come into contact. The equation of state of the polymer brush bilayers is obtained and it represents scaling of the pressure with molecular parameters and distance between substrates.
SIGNIFICANCEThe results of this study may shed light in our understanding of some severe Musloskeletal diseases which degrade the synovium. The significance of this study lays on the fact that the molecular structure is investigated through fundamental physical laws. So, this study bridges between theoretical biological physics and medicine. | biophysics |
Empirical single-cell tracking and cell-fate simulation reveal dual roles of p53 in tumor suppression The tumor suppressor p53 regulates various stress responses via increasing its cellular levels. The lowest p53 levels occur in unstressed cells; however, the functions of these low levels remains unclear. To investigate the functions, we used empirical single-cell tracking of p53-expressing (Control) cells and cells in which p53 expression was silenced by RNA interference (p53 RNAi). Here we show that p53 RNAi cells underwent more frequent cell death and cell fusion, which further induced multipolar cell division to generate aneuploid progeny. Those results suggest that the low levels of p53 in unstressed cells indeed have a role in suppressing the induction of cell death and the formation of aneuploid cells. We further investigated the impact of p53 silencing by developing an algorithm to simulate the fates of individual cells. Simulation of the fate of aneuploid cells revealed that these cells could propagate to create an aneuploid cell population. In addition, the simulation also revealed that more frequent induction of cell death in p53 RNAi cells under unstressed conditions conferred a growth disadvantage compared with Control cells, resulting in faster expansion of Control cells compared with p53 RNAi cells, leading to Control cells predominating in mixed cell populations. In contrast, growth of Control cells, but not p53 RNAi cells, was suppressed when the damage response was induced, allowing p53 RNAi cells to gain a growth advantage over Control cells. These results suggest that, although p53 could suppress the formation of aneuploid cells, which could have a role in tumorigenesis, it could also allow the expansion of cells lacking p53 expression when the damage response is induced. p53 may thus play a role in both the suppression and the promotion of malignant cell formation during tumorigenesis. | cell biology |
Identification and design of vinyl sulfone inhibitors against Cryptopain1-a cysteine protease from cryptosporidiosis-causing Cryptosporidium parvum Cryptosporidiosis, a disease marked by diarrhea in adults and stunted growth in children, is associated with the unicellular protozoan pathogen Cryptosporidium; often the species parvum. Cryptopain-1, a cysteine protease characterized in the genome of Cryptosporidium parvum, had been earlier shown to be inhibited by a vinyl sulfone compound called K11777 (or K-777). Cysteine proteases have long been established as valid drug targets, which can be covalently and selectively inhibited by vinyl sulfones. This computational study was initiated to identify purchasable vinyl sulfone compounds, which could possibly inhibit cryptopain-1 with higher efficacy than K11777. Docking simulations screened a number of such possibly better inhibitors. The work was furthered to probe the enzymatic pocket of cryptopain-1, through in-silico mutations, to derive a map of receptor-ligand interactions in the docked complexes. The idea was to provide crucial clues to aid the design of inhibitors, which would be able to bind the protease well by making favorable interactions with important residues of the enzyme. The analyses dictated placement of ligands towards the front of the enzymatic cleft, and disfavored interactions deep within. The S1 and S2 subsites of the enzyme preferred to remain occupied by polar ligand subgroups. Reasonably distanced ring systems and polar backbones of ligands were desired across the cleft. Large as well as inflexible subgroups were not tolerated. Double ringed systems such as substituted napthalene, especially in S1, were exceptions though. The S2 subsite, which is typically a specificity determinant in papain (C1) family cysteine proteases such as cathepsin L-like cryptopain-1, can possibly accommodate polar and hydrophobic ligand subgroups alike. | bioinformatics |
Spatial RNA sequencing identifies robust markers of vulnerable and resistant human midbrain dopamine neurons and their expression in Parkinson's Disease Defining transcriptional profiles of substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) dopamine neurons is critical to understanding their differential vulnerability in Parkinsons Disease (PD). Here, we determine transcriptomes of human SNc and VTA dopamine neurons using LCM-seq on a large sample cohort. We apply a bootstrapping strategy as sample input to DESeq2 and identify 33 stably differentially expressed genes (DEGs) between these two subpopulations. We also compute a minimal sample size for identification of stable DEGs, which highlights why previous reported profiles from small sample sizes display extensive variability. Network analysis reveal gene interactions unique to each subpopulation and highlight differences in regulation of mitochondrial stability, apoptosis, neuronal survival, cytoskeleton regulation, extracellular matrix modulation and well as synapse integrity, which could explain the relative resilience of VTA dopamine neurons. Analysis of PD tissues showed that while identified stable DEGs can distinguish the subpopulations also in disease, the SNc markers SLIT1 and ATP2A3 were downregulated and thus appears to be biomarkers of disease. In summary, our study identifies human SNc and VTA marker profiles, which will be instrumental for studies aiming to modulate dopamine neuron resilience and to validate cell identity of stem cell-derived dopamine neurons. | neuroscience |
Dissociating Language and Thought in Human Reasoning What is the relationship between natural language and complex thought? In the context of complex reasoning, there are two main views. Under the first, language is central to the syntax-like combinatorial operations necessary for complex reasoning. Under the second, these operations are independent of the mechanisms of natural language. We used noninvasive neuromodulation, in the form of continuous theta burst stimulation, to transiently inhibit Brocas area, a region associated in prior research with parsing the syntactic relations of natural language, and dorsomesial frontal cortex, a region previously described as core for logical reasoning. The dissociative hypothesis of language and deductive reasoning predicts an interaction between stimulated areas and tested functions, which we observed. Transient inhibition of Brocas area significantly disrupted linguistic processing without affecting deductive reasoning. The reverse pattern was seen for transient inhibition of dorsomesial frontal cortex, albeit not reaching significance. These results are evidence for the independence of abstract complex reasoning from natural language in the adult brain. | neuroscience |
Broad geographic sampling reveals predictable, pervasive, and strong seasonal adaptation in Drosophila To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila. | evolutionary biology |
3D Reconstruction of Bird Flight Using a Single Video Camera Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the position of the bird at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field. | animal behavior and cognition |
The interspecific fungal hybrid Verticillium longisporum displays sub-genome-specific gene expression Hybridization is an important evolutionary mechanism that can enable organisms to adapt to environmental challenges. It has previously been shown that the fungal allodiploid species Verticillium longisporum, causal agent of Verticillium stem striping in rape seed, has originated from at least three independent hybridization events between two haploid Verticillium species. To reveal the impact of genome duplication as a consequence of the hybridization, we studied the genome and transcriptome dynamics upon two independent V. longisporum hybridization events, represented by the hybrid lineages "A1/D1" and "A1/D3". We show that the V. longisporum genomes are characterized by extensive chromosomal rearrangements, including between parental chromosomal sets. V. longisporum hybrids display signs of evolutionary dynamics that are typically associated with the aftermath of allodiploidization, such as haploidization and a more relaxed gene evolution. Expression patterns of the two sub-genomes within the two hybrid lineages are more similar than those of the shared A1 parent between the two lineages, showing that expression patterns of the parental genomes homogenized within a lineage. However, as genes that display differential parental expression in planta do not typically display the same pattern in vitro, we conclude that sub-genome-specific responses occur in both lineages. Overall, our study uncovers the genomic and transcriptomic plasticity during evolution of the filamentous fungal hybrid V. longisporum and illustrate its adaptive potential.
ImportanceVerticillium is a genus of plant-associated fungi that include a handful of plant pathogens that collectively affect a wide range of hosts. On several occasions, haploid Verticillium species hybridized into the stable allodiploid species Verticillium longisporum, which is, in contrast to haploid Verticillium species, a Brassicaceae specialist. Here, we studied the evolutionary genome and transcriptome dynamics of V. longisporum and the impact of the hybridization. V. longisporum genomes display a mosaic structure due do genomic rearrangements between the parental chromosome sets. Similar to other allopolyploid hybrids, V. longisporum displays an ongoing loss of heterozygosity and a more relaxed gene evolution. Also, differential parental gene expression is observed, with an enrichment for genes that encode secreted proteins. Intriguingly, the majority of these genes displays sub-genome-specific responses under differential growth conditions. In conclusion, hybridization has incited the genomic and transcriptomic plasticity that enables adaptation to environmental changes in a parental allele-specific fashion. | microbiology |
Ecological Network assembly: how the regional meta web influence local food webs O_LILocal food webs result from a sequence of colonisations and extinctions by species from the regional pool or metaweb, i.e., the assembly process. Assembly is theorised to be a selective process: whether or not certain species or network structures can persist is partly determined by local processes including habitat filtering and dynamical constraints. Consequently, local food web structure should reflect these processes.
C_LIO_LIThe goal of this study was to test evidence for these selective processes by comparing the structural properties of real food webs to the expected distribution given the metaweb. We were particularly interested in ecological dynamics; if the network properties commonly associated with dynamical stability are indeed the result of stability constraints, then they should deviate from expectation in the direction predicted by theory.
C_LIO_LITo create a null expectation, we used the novel approach of randomly assembling model webs by drawing species and interactions from the empirical metaweb. The assembly model permitted colonisation and extinction, and required a consumer species to have at least one prey, but had no habitat type nor population dynamical constraints. Three data sets were used: (1) the marine Antarctic metaweb, with 2 local food-webs; (2) the 50 lakes of the Adirondacks; and (3) the arthropod community from Florida Keys classic defaunation experiment.
C_LIO_LIContrary to our expectations, we found that there were almost no differences between empirical webs and those resulting from the null assembly model. Few empirical food webs showed significant differences with network properties, motif representations and topological roles. Network properties associated with stability did not deviate from expectation in the direction predicted by theory.
C_LIO_LIOur results suggest that -- for the commonly used metrics we considered -- local food web structure is not strongly influenced by dynamical nor habitat restrictions. Instead, the structure is inherited from the metaweb. This suggests that the network properties typically attributed as causes or consequences of ecological stability are instead a by-product of the assembly process (i.e., spandrels), and may potentially be too coarse to detect the true signal of dynamical constraint.
C_LI | ecology |
Network Reconstruction from Perturbation Time Course Data Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible. | systems biology |
Rapid adaptation of endocytosis, exocytosis and eisosomes after an acute increase in membrane tension in yeast cells During clathrin-mediated endocytosis in eukaryotes, actin assembly is required to overcome large membrane tension and turgor pressure. However, the molecular mechanisms by which the actin machinery adapts to varying membrane tension remain unknown. In addition, how cells reduce their membrane tension when they are challenged by hypotonic shocks remains unclear. We used quantitative microscopy to demonstrate that cells rapidly reduce their membrane tension using three parallel mechanisms. In addition to using their cell wall for mechanical protection, yeast cells disassemble eisosomes to buffer moderate changes in membrane tension on a minute time scale. Meanwhile, a temporary reduction of the rate of endocytosis for 2 to 6 minutes, and an increase in the rate of exocytosis for at least 5 minutes allow cells to add large pools of membrane to the plasma membrane. We built on these results to submit the cells to abrupt increases in membrane tension and determine that the endocytic actin machinery of fission yeast cells rapidly adapts to perform clathrin-mediated endocytosis. Our study sheds light on the tight connection between membrane tension regulation, endocytosis and exocytosis. | cell biology |
Evolutionary forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were also changed compared to the SBW25 system to test the robustness of forecasts to environmental variation. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including that of an uncharacterized polysaccharide operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spots were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.
Author SummaryBiological evolution is often repeatable in the short-term suggesting the possibility of forecasting and controlling evolutionary outcomes. In addition to its fundamental importance for biology, evolutionary processes are at the core of several major societal problems, including infectious diseases, cancer and adaptation to climate change. Experimental evolution allows study of evolutionary processes in real time and seems like an ideal way to test the predictability of evolution and our ability to make forecasts. However, lack of model systems where forecasts can be extended to other species evolving under different conditions has prevented studies that first predict evolutionary outcomes followed by direct testing. We showed that a well-characterized bacterial experimental evolution system, based on biofilm formation by Pseudomonas fluorescens at the surface of static growth tubes, can be extended to the related species Pseudomonas protegens. We tested evolutionary forecasts experimentally and showed that mutations mainly appear in the predicted genes resulting in similar phenotypes. We also identified factors that we cannot yet predict, such as variation in mutation rates and differences in fitness. Finally, we make forecasts for other Pseudomonas species to be tested in future experiments. | evolutionary biology |
KChIP4a selectively controls mesolimbic dopamine neuron inhibitory integration and learning from negative prediction errors Midbrain dopamine (DA) neurons are essential for multiple behaviors. DA neurons that project to different regions also have unique biophysical properties, and it is thought that this diversity reflects specializations to particular computational functions. If this is true, there should be specific genetic determinants of this heterogeneity whose manipulation would lead to circumscribed impacts on behavior. We test this general hypothesis by homing in on one particular mechanism using a new transgenic model and a combination of molecular, electrophysiological, computational, and behavioral approaches. We demonstrate that KChIP4a, a singular Kv4 {beta}-subunit splice variant, determines the long hyperpolarization-rebound delays observed in nucleus accumbens core-projecting DA neurons, that this biophysical switch controls the efficacy of inhibitory inputs to pause firing and, congruently, selectively regulates learning from negative prediction errors. Our results reveal a highly specialized gene-to-behavior mechanistic chain within the DA system, illuminating how cellular diversity shapes information processing in this key neuronal population.
Graphical abstract
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[email protected]@cad6d6org.highwire.dtl.DTLVardef@de8957org.highwire.dtl.DTLVardef@aedc6_HPS_FORMAT_FIGEXP M_FIG C_FIG | neuroscience |
A pragmatic approach to make theoretical syntheses in ecology Theoretical syntheses have the role of describing and guiding knowledge generation, and are usually done by enunciating the conceptual bases that guide research in a given field. In fields that develop axiomatically, the conceptual basis can be easily identified in the set of axioms guiding model building. However, ecology does not develop axiomatically but rather pragmatically, i.e., ecologists do not build models based on a predefined set of assumptions (axioms). They rather resort to any information that seems useful to learn about ecological phenomena. Therefore, a theoretical synthesis in ecology cannot rely on the enunciation of axioms; instead, it requires identifying what information and knowledge ecologists use (i.e., what they decide is useful to learn). Here we present an approach for producing theoretical syntheses based on the information/knowledge most frequently used to learn about the world. The approach consists of (i) defining a phenomenon of interest; (ii) defining a collective of scientists studying the phenomenon; (iii) surveying the scientific studies about the phenomenon published by this collective; (iv) identifying the most relevant publications used in these studies; (v) identifying how the studies refer to the most relevant publications; (vi) synthesizing what is being used by this collective to learn about the phenomenon. We implemented the approach in a case study on the phenomenon of ecological succession, defining the collective as the scientists currently studying succession. We identified three propositions that synthesize the views of the defined collective about succession. The theoretical synthesis revealed that there is no clear division between "classical" and "contemporary" succession models, and that neutral models are being used to explain successional patterns alongside with models based on niche assumptions.By implementing the pragmatic approach in a case study, we show that it can be successfully used to produce syntheses describing the conceptual bases of a field, which have the potential to guide knowledge generation. As such, these syntheses fulfil the roles ascribed to scientific theories in the epistemological literature. | ecology |
Microbial adaptation to venom is common in snakes and spiders Animal venoms are considered sterile sources of antimicrobial compounds with strong membrane disrupting activity against multi-drug resistant bacteria. However, bite wound infections are common in developing nations. Investigating the oral and venom microbiome of five snake and two spider species, we evidence viable microorganisms potentially unique to venom for black-necked spitting cobras (Naja nigricollis). Among these are two venom-resistant novel sequence types of Enterococcus faecalis; the genome sequence data of these isolates feature an additional 45 genes, nearly half of which improve membrane integrity. Our findings challenge the dogma of venom sterility and indicate an increased primary infection risk in the clinical management of venomous animal bite wounds.
One Sentence SummaryIndependent bacterial colonization of cobra venom drives acquisition of genes antagonistic to venom antimicrobial peptides. | microbiology |
The Goldilocks Effect: Female geladas in mid-sized groups have higher fitness The cost-benefit ratio of group-living is thought to vary with group size: individuals in "optimally-sized" groups should have higher fitness than individuals in groups that are either too large or too small. However, the relationship between group size and individual fitness has been difficult to establish for long-lived species where the number of groups studied is typically quite low. Here we present evidence for optimal group size that maximizes female fitness in a population of geladas (Theropithecus gelada). Drawing on 14 years of demographic data, we found that females in small groups experienced the highest death rates, while females in mid-sized units exhibited the highest reproductive performance. This group-size effect on female reproductive performance was largely explained by variation in infant mortality (and, in particular, by infanticide from immigrant males) but not by variation in reproductive rates. Taken together, females in mid-sized units are projected to attain optimal fitness due to conspecific infanticide and, potentially, predation. Our findings provide insight into how and why group size shapes fitness in long-lived species. | evolutionary biology |
Joint inference of species histories and gene flow When populations become isolated, members of these populations can diverge genetically over time. This leads to genetic differences between these populations that increase over time if the isolation persists. This process can be counteracted by gene flow, i.e. when genes are exchanged between populations. In order to study the speciation processes when gene flow is present, isolation-with-migration methods have been developed. These methods typically assume that the ranked topology of the species history is already known. However, this is often not the case and the species tree is therefore of interest itself. For the inference of species trees, it is in turn often necessary to assume that there is no gene flow between co-existing species. This assumption, however, can lead to wrongly inferred speciation times and species tree topologies. We here introduce a new method that allows inference of the species tree while explicitly modelling the flow of genes between coexisting species. By using Markov chain Monte Carlo sampling, we co-infer the species tree alongside evolutionary parameters of interest. By using simulations, we show that our newly introduced approach is able to reliably infer the species trees and parameters of the isolation-with-migration model from genetic sequence data. We then use this approach to infer the species history of the mosquitoes from the Anopheles gambiae species complex. Accounting for gene flow when inferring the species history suggests a slightly different speciation order and gene flow than previously suggested. | evolutionary biology |
5' Modifications Improve Potency and Efficacy of DNA Donors for Precision Genome Editing Nuclease-directed genome editing is a powerful tool for investigating physiology and has great promise as a therapeutic approach to correct mutations that cause disease. In its most precise form, genome editing can use cellular homology-directed repair (HDR) pathways to insert information from an exogenously supplied DNA repair template (donor) directly into a targeted genomic location. Unfortunately, particularly for long insertions, toxicity and delivery considerations associated with repair template DNA can limit HDR efficacy. Here, we explore chemical modifications to both double-stranded and single-stranded DNA-repair templates. We describe 5'-terminal modifications, including in its simplest form the incorporation of triethylene glycol (TEG) moieties, that consistently increase the frequency of precision editing in the germlines of three animal models (Caenorhabditis elegans, zebrafish, mice) and in cultured human cells. | molecular biology |
Structure-aware M. tuberculosis functional annotation uncloaks resistance, metabolic, and virulence genes Accurate and timely functional genome annotation is essential for translating basic pathogen research into clinically impactful advances. Here, through literature curation and structure-function inference, we systematically update the functional genome annotation of Mycobacterium tuberculosis virulent type strain H37Rv. First, we systematically curated annotations for 589 genes from 662 publications, including 282 gene products absent from leading databases. Second, we modeled 1,711 under-annotated proteins and developed a semi-automated pipeline that captured shared function between 400 protein models and structural matches of known function on protein data bank, including drug efflux proteins, metabolic enzymes, and virulence factors. In aggregate, these structure- and literature-derived annotations update 940/1,725 under-annotated H37Rv genes and generate hundreds of functional hypotheses. Retrospectively applying the annotation to a recent whole-genome transposon mutant screen provided missing function for 48% (13/27) of under-annotated genes altering antibiotic efficacy and 33% (23/69) required for persistence during mouse TB infection. Prospective application of the protein models enabled us to functionally interpret novel laboratory generated Pyrazinamide-resistant (PZA) mutants of unknown function, which implicated the emerging Coenzyme A depletion model of PZA action in the mutants PZA resistance. Our findings demonstrate the functional insight gained by integrating structural modeling and systematic literature curation, even for widely studied microorganisms. Functional annotations and protein structure models are available at https://tuberculosis.sdsu.edu/H37Rv in human- and machine-readable formats.
IMPORTANCEMycobacterium tuberculosis, the primary causative agent of tuberculosis, kills more humans than any other infectious bacteria. Yet 40% of its genome is functionally uncharacterized, leaving much about the genetic basis of its resistance to antibiotics, capacity to withstand host immunity, and basic metabolism yet undiscovered. Irregular literature curation for functional annotation contributes to this gap. We systematically curated functions from literature and structural similarity for over half of poorly characterized genes, expanding the functionally annotated Mycobacterium tuberculosis proteome. Applying this updated annotation to recent in vivo functional screens added functional information to dozens of clinically pertinent proteins described as having unknown function. Integrating the annotations with a prospective functional screen identified new mutants resistant to a first-line TB drug supporting an emerging hypothesis for its mode of action. These improvements in functional interpretation of clinically informative studies underscores the translational value of this functional knowledge. Structure-derived annotations identify hundreds of high-confidence candidates for mechanisms of antibiotic resistance, virulence factors, and basic metabolism; other functions key in clinical and basic tuberculosis research. More broadly, it provides a systematic framework for improving prokaryotic reference annotations. | genomics |
Distracting Linguistic Information Impairs Neural Tracking of Attended Speech Listening to speech is difficult in noisy environments, and is even harder when the interfering noise consists of intelligible speech as compared to unintelligible sounds. This suggests that the competing linguistic information interferes with the neural processing of target speech. Interference could either arise from a degradation of the neural representation of the target speech, or from increased representation of distracting speech that enters in competition with the target speech. We tested these alternative hypotheses using magnetoencephalography (MEG) while participants listened to a target clear speech in the presence of distracting noise-vocoded speech. Crucially, the distractors were initially unintelligible but became more intelligible after a short training session. Results showed that the comprehension of the target speech was poorer after training than before training. The neural tracking of target speech in the delta range (1-4 Hz) reduced in strength in the presence of a more intelligible distractor. In contrast, the neural tracking of distracting signals was not significantly modulated by intelligibility. These results suggest that the presence of distracting speech signals degrades the linguistic representation of target speech carried by delta oscillations. | neuroscience |
Extracellular histones, a new class of inhibitory molecules of CNS axonal regeneration Axonal regeneration in the mature CNS is limited by extracellular inhibitory factors. Triple knockout mice lacking the major myelin-associated inhibitors do not display spontaneous regeneration after injury, indicating the presence of other inhibitors. Searching for such inhibitors we have detected elevated levels of histone H3 in human cerebrospinal fluid (CSF) 24 hours after spinal cord injury. Following dorsal column lesions in mice and optic nerve crushes in rats, elevated levels of extracellular histone H3 were detected at the injury site. Similar to myelin-associated inhibitors, these extracellular histones induced growth cone collapse and inhibited neurite outgrowth. Histones mediate inhibition through the transcription factor YB-1 and Toll-like receptor 2, and these effects are independent of the Nogo receptor. Histone-mediated inhibition can be reversed by the addition of activated protein C (APC) in vitro, and APC treatment promotes axonal regeneration in the crushed optic nerve in vivo. These findings identify extracellular histones as a new class of nerve regeneration-inhibiting molecules within the injured CNS.
One sentence summaryProteins typically associated with chromatin structure play an unexpected role in limiting axonal regeneration after injury. | neuroscience |
Dispensing a synthetic green leaf volatile to two plant species in a common garden differentially alters physiological responses and herbivory Herbivore-induced plant volatile (HIPV)-mediated eavesdropping by plants is a well-documented, inducible phenomenon that has practical agronomic applications for enhancing plant defense and pest management. However, as with any inducible phenomenon, responding to volatile cues may incur physiological and ecological costs that limit plant productivity. In a common garden experiment, we tested the hypothesis that exposure to a single HIPV would decrease herbivore damage at the cost of reduced plant growth and reproduction. Lima bean (Phaseolus lunatus) and pepper (Capsicum annuum) plants were exposed to a persistent, low-dose ([~]10ng/hour) of the green leaf volatile cis-3-hexenyl acetate (z3HAC), which is an HIPV and damage-associated volatile. z3HAC-treated pepper plants were shorter, had less aboveground and belowground biomass, and produced fewer flowers and fruits relative to controls while z3HAC-treated lima bean plants were taller and produced more leaves and flowers than did controls. Natural herbivory was reduced in z3HAC-exposed lima bean plants, but not in pepper. Cyanogenic potential, a putative direct defense mechanism in lima bean, was lower in young z3HAC-exposed leaves, suggesting a growth-defense tradeoff from z3HAC exposure alone. Plant species-specific responses to an identical volatile cue have important implications for agronomic costs and benefits of volatile-mediated inter-plant communication under field conditions. | ecology |
The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes AO_SCPLOWBSTRACTC_SCPLOWStrong trophic interactions link primary producers (phytoplankton) and consumers (zooplankton) in lakes. However, the influence of such interactions on the biogeographical distribution of the taxa and functional traits of planktonic organisms in lakes has never been explicitly tested. To better understand the spatial distribution of these two major aquatic groups, we related composition across boreal lakes (104 for zooplankton and 48 for phytoplankton) in relation to a common suite of environmental and spatial factors. We then directly tested the degree of coupling in their taxonomic and functional distributions across the subset of common lakes. Although phytoplankton composition responded mainly to properties related to water quality while zooplankton composition responded more strongly to lake morphometry, we found significant coupling between their spatial distributions at taxonomic and functional levels based on a Procrustes test. This coupling was not significant after removing the effect of environmental drivers (water quality and morphometry) on the spatial distributions of the two groups. This result suggests that top-down and bottom-up effects (e.g. nutrient concentration and predation) drove trophic interactions at the landscape level. We also found a significant effect of dispersal limitation on the distribution of taxa, which could explain why coupling was stronger for taxa than for traits at the scale of this study, with a turnover of species observed between regions, but no trait turnover. Our results indicate that landscape pelagic food web responses to anthropogenic changes in ecosystem parameters should be driven by a combination of top-down and bottom-factors for taxonomic composition, but with a relative resilience in functional trait composition of lake communities. | ecology |
Predicting subclinical psychotic-like experiences on a continuum using machine learning Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia patients and healthy controls. The aim of this study was to use electroencephalographic (EEG) data and pattern recognition to predict subclinical psychotic-like experiences on a continuum between these two extremes in otherwise healthy people. We applied two different approaches to an auditory oddball regularity learning task obtained from N = 73 participants:
O_LIA feature extraction and selection routine incorporating behavioural measures, event-related potential components and effective connectivity parameters;
C_LIO_LIRegularisation of spatiotemporal maps of event-related potentials.
C_LI
Using the latter approach, optimal performance was achieved using the response to frequent, predictable sounds. Features within the P50 and P200 time windows had the greatest contribution toward lower Prodromal Questionnaire (PQ) scores and the N100 time window contributed most to higher PQ scores. As a proof-of-concept, these findings demonstrate that EEG data alone are predictive of individual psychotic-like experiences in healthy people. Our findings are in keeping with the mounting evidence for altered sensory responses in schizophrenia, as well as the notion that psychosis may exist on a continuum expanding into the non-clinical population. | neuroscience |
Individuals with ventromedial frontal damage have more unstable but still fundamentally transitive preferences The ventromedial frontal lobes (VMF) are important for decision-making, but the precise causal role of the VMF in the decision process has not yet fully been established. Previous studies have suggested that individuals with VMF damage violate transitivity, a hallmark axiom of rational decisions. However, these prior studies cannot properly distinguish whether individuals with VMF damage are truly prone to choosing irrationally from whether their preferences are simply more variable. We had individuals with focal VMF damage, individuals with other frontal damage, and healthy controls make repeated choices across three categories - artwork, chocolate bar brands, and gambles. Using sophisticated tests of transitivity, we find that, without exception, individuals with VMF damage make rational decisions consistent with transitive preferences, even though they exhibit greater variability in their preferences. That is, the VMF is necessary for having strong and reliable preferences, but not for being a rational decision maker. VMF damage affects the noisiness with which value is assessed, but not the consistency with which value is sought. | neuroscience |
De Novo Mutational Signature Discovery in Tumor Genomes using SparseSignatures Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or "mutational signatures". Here we present SparseSignatures, a novel framework to extract signatures from somatic point mutation data. Our approach incorporates a user-specified background signature, employs regularization to reduce noise in non-background signatures, uses cross-validation to identify the number of signatures, and is scalable to large datasets. We show that SparseSignatures outperforms current state-of-the-art methods on simulated data using a variety of standard metrics. We then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms and are strongly associated with patient clinical features.
Authors SummaryCancer is a genetic disease, occurring as a result of mutagenic processes causing DNA somatic mutations in genes controlling cellular growth and division. These somatic mutations arise from processes such as defective DNA repair and environmental mutagens, which massively increase the rate of somatic variants. As a result, due to the specificity of molecular lesions caused by such processes, and the specific repair mechanisms deployed by the cell to mitigate the damage, mutagenic processes generate characteristic point mutation rate spectra which are called mutational signatures. These signatures can indicate which mutagenic processes are active in a tumor, reveal biological differences between cancer subtypes, and may be useful markers for therapeutic response. Here, we develop SparseSignatures, a novel framework for mutational signature discovery capable of both identifying the active signatures in a dataset of point mutations and calculating their exposure values, i.e., the number of mutations originating from each signature in each patient. We show that our approach outperforms current state-of-the-art methods on simulated data using a variety of standard metrics and then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms. | bioinformatics |
GranatumX: A community engaging, modularized and flexible software environment for single-cell analysis We present GranatumX, a next-generation software environment for single-cell data analysis. GranatumX is inspired by the interactive web tool Granatum. It enables biologists to access the latest single-cell bioinformatics methods in a web-based graphical environment. It also offers software developers the opportunity to rapidly promote their own tools with others in customizable pipelines. The architecture of GranatumX allows for easy inclusion of plugin modules, named Gboxes, that wrap around bioinformatics tools written in various programming languages and on various platforms. GranatumX can be run on the cloud or private servers and generate reproducible results. It is a community-engaging, flexible, and evolving software ecosystem for scRNA-Seq analysis, connecting developers with bench scientists. GranatumX is freely accessible at http://garmiregroup.org/granatumx/app. | bioinformatics |
High-quality SNPs from genic regions highlight introgression patterns among European white oaks (Quercus petraea and Q. robur). The Src homology-2 domain containing phosphatase SHP2 is a critical regulator of signal transduction, being implicated in cell growth and differentiation. Activating mutations cause developmental disorders and act as oncogenic drivers in hematologic cancers. SHP2 is activated by phosphopeptide binding to the N-SH2 domain, triggering the release of N-SH2 from the catalytic PTP domain. Based on early crystallographic data, it has been widely accepted that opening of the binding cleft of N-SH2 serves as the key "allosteric switch" driving SHP2 activation. To test the putative coupling between binding cleft opening and SHP2 activation as assumed by the "allosteric switch" model, we critically reviewed structural data of SHP2 and we used extensive molecular dynamics (MD) simulation and free energy calculations of isolated N-SH2 in solution, SHP2 in solution, and SHP2 in a crystal environment. Our results demonstrate that the binding cleft in N-SH2 is constitutively flexible and open in solution, and that a closed cleft found in certain structures is a consequence of crystal contacts. The degree of opening of the binding cleft has only a negligible effect on the free energy of SHP2 activation. Instead, SHP2 activation is greatly favored by the opening of the central {beta}- sheet of N-SH2. We conclude that opening of the N-SH2 binding cleft is not the key allosteric switch triggering SHP2 activation.
Significance StatementSHP2 is a multi-domain protein, playing an important role in up-regulating cellular processes such as cell survival, proliferation, and programmed cell death. SHP2 mutations cause developmental disorders and were found in many cancer types, including neuroblastoma, breast cancer, and leukemia. In healthy cells, SHP2 mainly takes an autoinhibited, inactive form, and SHP2 is activated upon binding of phosphopeptides to the N-SH2 domain. For the past two decades, the widening of the binding cleft upon peptide binding has been considered as the key event driving SHP2 activation. Here, by analyzing crystallographic data and molecular simulations, we demonstrate that the binding cleft in N-SH2 is, instead, already open and accessible in solution, and its degree of opening does not influence SHP2 activation. | evolutionary biology |
Eye movements during text reading align with the rate of speech production Across languages, the speech signal is characterized by a predominant modulation of the amplitude spectrum between about 4.3-5.5Hz, reflecting the production and processing of linguistic information chunks (syllables, words) every [~]200ms. Interestingly, [~]200ms is also the typical duration of eye fixations during reading. Prompted by this observation, we demonstrate that German readers sample written text at [~]5Hz. A subsequent meta-analysis with 142 studies from 14 languages replicates this result, but also shows that sampling frequencies vary across languages between 3.9Hz and 5.2Hz, and that this variation systematically depends on the complexity of the writing systems (character-based vs. alphabetic systems, orthographic transparency). Finally, we demonstrate empirically a positive correlation between speech spectrum and eye-movement sampling in low-skilled readers. Based on this convergent evidence, we propose that during reading, our brains linguistic processing systems imprint a preferred processing rate, i.e., the rate of spoken language production and perception, onto the oculomotor system. | neuroscience |
Basal ganglia and cortical control of thalamic rebound spikes Movement-related decreases in firing rate have been observed in basal ganglia output neurons. They may transmit motor signals to the thalamus, but the effect of these firing rate decreases on downstream neurons in the motor thalamus is not known. One possibility is that they lead to thalamic post-inhibitory rebound spikes. However, it has also been argued that the physiological conditions permitting rebound spiking are pathological, and primarily present in Parkinsons disease. As in Parkinsons disease neural activity becomes pathologically correlated, we investigated the impact of correlations in basal ganglia output on the transmission of motor signals using a Hodgkin-Huxley model of thalamocortical neurons. We found that such correlations disrupt the transmission of motor signals via rebound spikes by decreasing the signal-to-noise ratio and increasing the trial-to-trial variability. We further examined the role of sensory responses in basal ganglia output neurons and the effect of cortical excitation of motor thalamus in modulating rebound spiking. Interestingly, both could either promote or suppress the generation of rebound spikes depending on their timing relative to the motor signal. Finally, we determined parameter regimes, such as levels of excitation, under which rebound spiking is feasible in the model, and confirmed that the conditions for rebound spiking are primarily given in pathological regimes. However, we also identified specific conditions in the model that would allow rebound spiking to occur in healthy animals in a small subset of thalamic neurons. Overall, our model provides novel insights into differences between normal and pathological transmission of motor signals. | neuroscience |
Reduction in CD11c+ microglia correlates with clinical progression in chronic experimental autoimmune demyelination Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease with high variability of clinical symptoms. In most cases MS appears as a relapsing-remitting disease course that at a later stage transitions into irreversible progressive decline of neurologic function. The mechanisms underlying MS progression remain poorly understood. Experimental autoimmune encephalomyelitis (EAE) is an animal model of MS. Here we demonstrate that mice that develop mild EAE after immunization with myelin oligodendrocyte glycoprotein 35-55 are prone to undergo clinical progression around 30 days after EAE induction. EAE progression was associated with reduction in CD11c+ microglia and dispersed coalescent parenchymal infiltration. We found sex-dependent differences mediated by p38 signaling, a key regulator of inflammation. Selective reduction of CD11c+ microglia in female mice with CD11c-promoter driven p38 knockout (KO) correlated with increased rate of EAE progression. In protected animals, we found CD11c+ microglia forming contacts with astrocyte processes at the glia limitans and immune cells retained within perivascular spaces. Together, our study provides evidence on the protective role of CD11c+ microglia in controlling CNS immune cell parenchymal infiltration in autoimmune demyelination. | neuroscience |
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