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Transcriptomic analysis of human and mouse muscle during hyperinsulinemia demonstrates insulin receptor downregulation as a mechanism for insulin resistance Hyperinsulinemia is commonly viewed as a compensatory response to insulin resistance, yet studies have suggested that chronically elevated insulin may also drive insulin resistance. The molecular mechanisms underpinning this potentially cyclic process remain poorly defined, especially on a transcriptome-wide level. To study the direct effects of prolonged exposure to excess insulin in muscle cells, we incubated C2C12 myotubes with elevated insulin for 16 hours, followed by 6 hours of serum starvation, and established that acute AKT and ERK signaling were attenuated in this model of in vitro hyperinsulinemia. Global RNA-sequencing of cells both before and after nutrient withdrawal highlighted genes in the insulin signaling, FOXO signaling, and glucose metabolism pathways indicative of hyperinsulinemia and starvation programs. We observed that hyperinsulinemia led to a substantial reduction in insulin receptor (Insr) gene expression, and subsequently a reduced surface INSR and total INSR protein, both in vitro and in vivo. Transcriptomic meta-analysis in >450 human samples demonstrated that fasting insulin reliably and negatively correlated with insulin receptor (INSR) mRNA in skeletal muscle. Bioinformatic modeling combined with RNAi, identified SIN3A as a negative regulator of Insr mRNA (and JUND, MAX, and MXI as positive regulators of Irs2 mRNA). Together, our analysis identifies novel mechanisms which may explain the cyclic processes underlying hyperinsulinemia-induced insulin resistance in muscle, a process directly relevant to the etiology and disease progression of type 2 diabetes. | physiology |
Endocytosis against high turgor pressure is made easier by partial protein coating and a freely rotating base During clathrin-mediated endocytosis, a patch of flat plasma membrane is deformed into a vesicle. In walled cells, such as plants and fungi, the turgor pressure is high and pushes the membrane against the cell wall, thus hindering membrane internalization. In this paper, we study how a patch of membrane is deformed against turgor pressure by force and by curvature-generating proteins. We show that a large amount of force is needed to merely start deforming the membrane and an even larger force is needed to pull a membrane tube. The magnitude of these forces strongly depends on how the base of the membrane is constrained and how the membrane is coated with curvature-generating proteins. In particular, these forces can be reduced by partially but not fully coating the membrane patch with curvature-generating proteins. Our theoretical results show excellent agreement with experimental data.
SIGNIFICANCEYeast cells have been widely used as a model system to study clathrin-mediated endocytosis. The mechanics of membrane during endocytosis has been extensively studied mostly in low turgor pressure condition, which is relevant for mammalian cells but not for yeast cells. It has been suggested that as a result of high turgor pressure in yeast cells, a large amount of force is needed to drive the progress of the membrane invagination. In this paper, we investigated biologically relevant mechanisms to reduce the force requirement. We highlight the role of boundary conditions at the membrane base, which is a factor that has been largely ignored in previous studies. We also investigate the role of curvature-generating proteins and show that a large protein coat does not necessarily reduce the force barrier for endocytosis. | biophysics |
Negative Affect Induces Rapid Learning of Counterfactual Representations: A Model-based Facial Expression Analysis Approach Whether we are making life-or-death decisions or thinking about the best way to phrase an email, counterfactual emotions including regret and disappointment play an ever-present role in how we make decisions. Functional theories of counterfactual thinking suggest that the experience and future expectation of counterfactual emotions should promote goal-oriented behavioral change. Although many studies find empirical support for such functional theories, the generative cognitive mechanisms through which counterfactual thinking facilitates changes in behavior are underexplored. Here, we develop generative models of risky decision-making that extend regret and disappointment theory to experience-based tasks, which we use to examine how people incorporate counterfactual information into their decisions across time. Further, we use computer-vision to detect positive and negative affect (valence) intensity from participants faces in response to feedback, which we use to explore how experienced emotion may correspond to cognitive mechanisms of learning, outcome valuation, or exploration/exploitation--any of which could result in functional changes in behavior. Using hierarchical Bayesian modeling and Bayesian model comparison methods, we found that a model assuming: (1) people learn to explicitly represent and subjectively weight counterfactual outcomes with increasing experience, and (2) people update their counterfactual expectations more rapidly as they experience increasingly intense negative affect best characterized empirical data. Our findings support functional accounts of regret and disappointment and demonstrate the potential for generative modeling and model-based facial expression analysis to enhance our understanding of cognition-emotion interactions. | neuroscience |
Coding Triplets in the Transfer RNA acceptor Arm and Their Role in Present and Past tRNA Recognition The mechanism and evolution of the recognition scheme between key components of the translation system, i.e., tRNAs, synthetases and elongation factors, are fundamental issues in understanding the translation of genetic information into proteins. Statistical analysis of bacterial tRNA sequences reveals that for six amino acids, i.e. for Ala, Asp, Gly, His, Pro and Ser, a string of 10 nucleotides preceding the tRNA 3end, carries cognate coding triplets to nearly full extent. The triplets conserved in positions 63-67 are implicated in the recognition by EF-Tu, and those conserved in positions 68-72, in the identification of cognate tRNAs and their derived minihelices, by class IIa synthetases. These coding triplets are suggested to have primordial origin, being engaged in aminoacylation of prebiotic tRNAs and in the establishment of the canonical codon set. | genetics |
Internal noise measures in coarse and fine motion direction discrimination tasks, and the correlation with autism traits Motion perception is essential for visual guidance of behaviour and is known to be limited by both internal additive noise (arising from random fluctuations in neural activity), and by motion pooling (global integration of local motion signals across space). People with autism spectrum disorder (ASD) display abnormalities in motion processing, which has been linked to both elevated noise and abnormal pooling. However, to date, the impact of a third limit - induced internal noise (internal noise that scales up with increases is external noise) - has not been investigated in motion perception of any group. Here, we describe a new double-pass motion direction discrimination paradigm that quantifies additive noise, induced noise, and motion pooling. We measure the impact of induced noise on direction discrimination, which we ascribe to fluctuations in decision-related variables. We report that internal noise is higher individuals with high ASD traits only on coarse but not fine motion direction discrimination tasks. However, we report no significant correlations between autism traits, and additive noise, induced noise or motion pooling, in either task. We conclude that internal noise may be higher in individuals with many ASD traits, and that the assessment of induced internal noise is a useful way of exploring decision-related limits on motion perception, irrespective of ASD traits. | neuroscience |
Polymer brush bilayers under stationary shear motion at linear response regime: A theoretical approach Statistical mechanics is employed to tackle the problem of polymer brush bilayers under stationary shear motion. The article addresses, solely, the linear response regime in which the polymer brush bilayers behave very much similar to the Newtonian fluids. My approach to this long-standing problem split drastically from the work already published Kreer, T, Soft Matter, 12, 3479 (2016). It has been thought for many decades that the interpenetration between the brushes is source of the friction between the brush covered surfaces sliding over each other. Whiles, the present article strongly rejects the idea of interpenetration length in that issue. Instead, here, I show that structure of the whole system is significant in friction between brush covered surfaces and the interpenetration is absolutely insignificant. The results of this research would blow ones mind about how the polymer brush bilayers respond at small shear rates. | biophysics |
What the odor is not: Estimation by elimination Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not, rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway. | neuroscience |
The Cdc14 phosphatase controls resolution of recombination intermediates and crossover formation during meiosis Meiotic defects derived from incorrect DNA repair during gametogenesis can lead to mutations, aneuploidies and infertility. Coordinated resolution of meiotic recombination intermediates is required for crossover formation, ultimately necessary for accurate completion of both rounds of chromosome segregation. Numerous master kinases orchestrate the correct assembly and activity of the repair machinery. Although much less is known, reversal of phosphorylation events in meiosis must also be key to coordinate the timing and functionality of repair enzymes. Cdc14 is an evolutionarily conserved phosphatase required for the dephosphorylation of multiple CDK1 targets. Mutations that inactivate this phosphatase lead to meiotic failure, but until now it was unknown if Cdc14 plays a direct role in meiotic recombination. Here, we show that elimination of Cdc14 leads to severe defects in the processing and resolution of recombination intermediates, causing a drastic depletion of crossovers when other repair pathways are compromised. We also show that Cdc14 is required for correct activity and localization of the Holliday Junction resolvase Yen1/GEN1. We reveal that Cdc14 regulates Yen1 activity from meiosis I onwards, and this function is essential for crossover resolution in the absence of other repair pathways. We also demonstrate that Cdc14 and Yen1 are required to safeguard sister chromatid segregation during the second meiotic division, a late action that is independent of the earlier role in crossover formation. Thus, this work uncovers previously undescribed functions of Cdc14 in the regulation of meiotic recombination. | genetics |
The solution structure of Dead End bound to AU-rich RNA reveals an unprecedented mode of tandem RRM-RNA recognition required for mRNA regulation Dead End (DND1) is an RNA-binding protein essential for germline development through its role in post-transcriptional gene regulation. The molecular mechanisms behind selection and regulation of its targets are unknown. Here, we present the solution structure of DND1s tandem RNA Recognition Motifs (RRMs) bound to AU-rich RNA. The structure reveals how an NYAYUNN element is specifically recognized, reconciling seemingly contradictory sequence motifs discovered in recent genome-wide studies. RRM1 acts as a main binding platform, including atypical extensions to the canonical RRM fold. RRM2 acts cooperatively with RRM1, capping the RNA using an unusual binding pocket, leading to an unprecedented mode of tandem RRM-RNA recognition. We show that the consensus motif is sufficient to mediate upregulation of a reporter gene in human cells and that this process depends not only on RNA binding by the RRMs, but also on DND1s double-stranded RNA binding domain (dsRBD), which is dispensable for target binding in cellulo. Our results point to a model where DND1 target selection is mediated by a non-canonical mode of AU-rich RNA recognition by the tandem RRMs and a role for the dsRBD in the recruitment of effector complexes responsible for target regulation. | molecular biology |
Conserving unprotected important coastal habitats in the Yellow Sea: shorebird occurrence, distribution and food resources at Lianyungang The authors have withdrawn their manuscript since this preprint contain errors which have been corrected in the version published in the journal Global Ecology and Conservation (doi: 10.1016/j.gecco.2019.e00724). Therefore, the authors do not wish this preprint to be cited as reference for the project. If you have any questions, please contact the corresponding author. | ecology |
Eco-evolutionary dynamics further weakens mutualistic interaction and coexistence under population decline AO_SCPLOWBSTRACTC_SCPLOWWith current environmental changes, evolution can rescue declining populations, but what happens to their interacting species? Mutualistic interactions can help species sustain each other when their environment worsens. However, mutualism is often costly to maintain, and evolution might counter-select it when not profitable enough. We investigate how evolution of mutualism affects the coexistence of two mutualistic species, e.g. a plant-pollinator or plant-fungi system. Specifically, using eco-evolutionary dynamics, we study the evolution of the focal species investment in the mutualistic interaction of a focal species (e.g. plant attractiveness via flower or nectar production for pollinators or carbon exudate for mycorrhizal fungi), and how it is affected by the decline of the partner population with which it is interacting. We assume an allocation trade-off so that investment in the mutualistic interaction reduces the species intrinsic growth rate. First, we investigate how evolution changes species persistence, biomass production, and the intensity of the mutualistic interaction. We show that concave trade-offs allow evolutionary convergence to stable coexistence. We next assume an external disturbance that decreases the partner population by lowering its intrinsic growth rate. Such declines result in the evolution of lower investment of the focal species in the mutualistic interaction, which eventually leads to the extinction of the partner species. With asymmetric mutualism favouring the partner, the evolutionary disappearance of the mutualistic interaction is delayed. Our results suggest that evolution may account for the current collapse of some mutualistic system like plant-pollinator ones, and that restoration attempts should be enforced early enough to prevent potential negative effects driven by evolution. | ecology |
Event segmentation reveals working memory forgetting rate We encounter the world as a continuous flow and effortlessly segment sequences of events into episodes. This process of event segmentation engages working memory (WM) for tracking the flow of events and impacts subsequent memory accuracy. WM is limited in how much information is retained (i.e., WM capacity) and for how long the information is retained (i.e., forgetting rate). It is unclear which aspect of WM limitations affects event segmentation. In two separate experiments with multiple tasks, we estimated participants WM capacity and forgetting rate in a dynamic context and evaluated their relationship to event segmentation. The results across tasks show that individuals who reported more movie segments than others (fine-segmenters) have a faster decaying WM. A separate task assessing long-term memory retrieval reveals that the coarse-segmenters have better recognition of temporal order of events in contrast to the fine-segmenters who performed better at free recall. The findings show that event segmentation employs dissociable memory strategies and depends on how long information is retained in WM. | neuroscience |
Recombination-independent recognition of DNA homology for meiotic silencing in Neurospora crassa Pairing of homologous chromosomes represents a critical step of meiosis in nearly all sexually reproducing species. While in some organisms meiotic pairing requires programmed DNA breakage and recombination, in many others it engages homologous chromosomes that remain apparently intact. The mechanistic nature of such recombination-independent pairing represents a fundamental question in molecular genetics. Using meiotic silencing by unpaired DNA (MSUD) in Neurospora crassa as a model process, we demonstrate the existence of a cardinally different approach to DNA homology recognition in meiosis. The main advantage of MSUD over other experimental systems lies in its ability to identify any relatively short DNA fragment lacking a homologous allelic partner. Here we show that MSUD does not rely on the canonical mechanism of meiotic recombination, yet it is promoted by REC8, a conserved component of the meiotic cohesin complex. We also show that certain patterns of interspersed homology are recognized as pairable during MSUD. Such patterns need to be co-linear and must contain short tracts of sequence identity spaced apart with a periodicity of 21 or 22 base-pairs. By using these values as a guiding parameter in all-atom molecular modeling, we discover that homologous double-stranded DNA molecules can associate by forming quadruplex-based contacts with an interval of 2.5 helical turns, which requires right-handed plectonemic coiling and additional conformational changes in the intervening double-helical segments. These results (i) reconcile genetic and biophysical lines of evidence for the existence of direct homologous dsDNA-dsDNA pairing, (ii) identify a role for this process in initiating post-transcriptional silencing, and (iii) suggest that chromosomes are cross-matched in meiosis by a precise mechanism that operates on intact double-stranded DNA molecules. | molecular biology |
Publicly available transcriptomes provide the opportunity for dual RNA-Seq meta analysis in Plasmodium infection Dual RNA-Seq is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic or gene regulatory pathways in addition to physically interacting proteins. Often, malaria studies address one of the interacting organisms - host or parasite - rendering the other "contamination". Here we perform a meta-analysis using such studies for cross-species expression analysis.
We screened experiments for gene expression from host and Plasmodium. Out of 171 studies in Homo sapiens, Macaca mulatta and Mus musculus, we identified 63 potential studies containing host and parasite data. While 16 studies (1950 samples) explicitly performed dual RNA-Seq, 47 (1398 samples) originally focused on one organism. We found 915 experimental replicates from 20 blood studies to be suitable for co-expression analysis and used orthologs for meta-analysis across different host-parasite systems. Centrality metrics from the derived gene expression networks correlated with gene essentiality in the parasites. We found indications of host immune response to elements of the Plasmodium protein degradation system, an antimalarial drug target. We identified well-studied immune responses in the host with our co-expression networks as our approach recovers known broad processes interlinked between hosts and parasites in addition to individual host and parasite protein associations.
The set of core interactions represents commonalities between human malaria and its model systems for prioritization in laboratory experiments. Our approach might also allow insights into the transferability of model systems for different pathways in malaria studies.
ImportanceMalaria still causes about 400,000 deaths a year and is one the most studied infectious diseases. The disease is studied in mice and monkeys as lab models to derive potential therapeutic intervention in human malaria. Interactions between Plasmodium spp. and its hosts are either conserved across different host-parasite systems or idiosyncratic to those systems. Here we use correlation of gene expression from different RNA-Seq studies to infer common host-parasite interactions across human, mouse and monkey studies. We, firstly, find a set of very conserved interactors, worth further scrutiny in focussed laboratory experiments. Secondly, this work might help assess to which extent experiments and knowledge on different pathways can be transferred from models to humans for potential therapy. | bioinformatics |
Common variants associated with OSMR expression contribute to carotid plaque vulnerability, but not to cardiovascular disease in humans Background and aimsOncostatin M (OSM) signaling is implicated in atherosclerosis, however the mechanism remains unclear. We investigated the impact of common genetic variants in OSM and its receptors, OSMR and LIFR, on overall plaque vulnerability, plaque phenotype, intraplaque OSMR and LIFR expression, coronary artery calcification burden and cardiovascular disease susceptibility.
Methods and resultsWe queried Genotype-Tissue Expression data and found that rs13168867 (C allele) was associated with decreased OSMR expression and that rs10491509 (A allele) was associated with increased LIFR expression in arterial tissues. No variant was significantly associated with OSM expression.
We associated these two variants with plaque characteristics from 1,443 genotyped carotid endarterectomy patients in the Athero-Express Biobank Study. After correction for multiple testing, rs13168867 was significantly associated with an increased overall plaque vulnerability ({beta}=0.118 {+/-} s.e.=0.040, p=3.00x10-3, C allele). Looking at individual plaque characteristics, rs13168867 showed strongest associations with intraplaque fat ({beta}=0.248 {+/-} s.e.=0.088, p=4.66 x 10-3, C allele) and collagen content ({beta}=-0.259 {+/-} s.e.=0.095, p=6.22 x 10-3, C allele), but these associations were not significant after correction for multiple testing. rs13168867 was not associated with intraplaque OSMR expression. Neither was intraplaque OSMR expression associated with plaque vulnerability and no known OSMR eQTLs were associated with coronary artery calcification burden, or cardiovascular disease susceptibility. No associations were found for rs10491509 in the LIFR locus.
ConclusionsOur study suggests that rs1316887 in the OSMR locus is associated with increased plaque vulnerability, but not with coronary calcification or cardiovascular disease risk. It remains unclear through which precise biological mechanisms OSM signaling exerts its effects on plaque morphology. However, the OSM-OSMR/LIFR pathway is unlikely to be causally involved in lifetime cardiovascular disease susceptibility. | genetics |
Liver X Receptor; Controls Hepatic Stellate Cell Activation via Hedgehog Signaling Liver X receptors (LXR) and {beta} serve important roles in cholesterol homeostasis, anti-inflammatory processes and the activation of hepatic stellate cells (HSCs). However, the development of therapies for liver fibrosis based on LXR agonists have been hampered due to side-effects such as liver steatosis. In this study, we demonstrated that HSCs expressed high levels of LXR{beta}, but not LXR, and that overexpression of LXR{beta} suppressed fibrosis and HSC activation in a carbon tetrachloride (CCl4)-induced fibrosis mouse model, without resulting in liver steatosis. Furthermore, Hedgehog (Hh)-regulated proteins, markedly increased in the CCl4-affected liver and mainly expressed in activated HSCs, were repressed under conditions of LXR{beta} overexpression. In addition, LXR{beta} knockout led to activation of Hh signaling and triggering of HSC activation, while overexpression of LXR{beta} led to the inhibition of the Hh pathway and suppression of HSC activation. These results suggest that LXR{beta} suppresses the activation mechanism of HSCs by inhibiting Hh signaling. In conclusion, LXR{beta}, by restoring the differentiation of HSCs, may be a promising therapeutic target for liver fibrosis without the adverse side-effects of LXR activation. | cell biology |
Balancing selection of the Intracellular Pathogen Response in natural Caenorhabditis elegans populations Genetic variation in host populations may lead to differential viral susceptibilities. Here, we investigate the role of natural genetic variation in the Intracellular Pathogen Response (IPR), an important antiviral pathway in the model organism Caenorhabditis elegans against Orsay virus (OrV). The IPR involves transcriptional activity of 80 genes including the pals-genes. We examine the genetic variation in the pals-family for traces of selection and explore the molecular and phenotypic effects of having distinct pals-gene alleles. Genetic analysis of 330 global C. elegans strains reveals that genetic diversity within the IPR-related pals-genes can be categorized in a few haplotypes worldwide. Importantly, two key IPR regulators, pals-22 and pals-25, are in a genomic region carrying signatures of balancing selection, suggesting that different evolutionary strategies exist in IPR regulation. We infected eleven C. elegans strains that represent three distinct pals-22 pals-25 haplotypes with Orsay virus to determine their susceptibility. For two of these strains, N2 and CB4856, the transcriptional response to infection was also measured. The results indicate that pals-22 pals-25 haplotype shapes the defense against OrV and host genetic variation can result in constitutive activation of IPR genes. Our work presents evidence for balancing genetic selection of immunity genes in C. elegans and provides a novel perspective on the functional diversity that can develop within a main antiviral response in natural host populations. | genetics |
A candidate causal variant underlying both enhanced cognitive performance and increased risk of bipolar disorder Bipolar disorder is a highly heritable mental illness, but the relevant genetic variants and molecular mechanisms are largely unknown. Recent GWASs have identified an intergenic region associated with both cognitive performance and bipolar disorder. This region contains dozens of putative fetal brain-specific enhancers and is located [~]0.7 Mb upstream of the neuronal transcription factor POU3F2. We identified a candidate causal variant, rs77910749, that falls within a highly conserved putative enhancer, LC1. This human-specific variant is a single-base deletion in a PAX6 binding site and is predicted to be functional. We hypothesized that rs77910749 alters LC1 activity and hence POU3F2 expression during neurodevelopment. Indeed, transgenic reporter mice demonstrated LC1 activity in the developing cerebral cortex and amygdala. Furthermore, ex vivo reporter assays in embryonic mouse brain and human iPSC-derived cerebral organoids revealed increased enhancer activity conferred by the variant. To probe the in vivo function of LC1, we deleted the orthologous mouse region, which resulted in amygdala-specific changes in Pou3f2 expression. Lastly, humanized rs77910749 knock-in mice displayed behavioral defects in sensory gating, an amygdala-dependent endophenotype seen in patients with bipolar disorder. Our study suggests a molecular mechanism underlying the long-speculated link between enhanced cognitive performance and neuropsychiatric disease. | genetics |
PME-1 suppresses anoikis, and is associated with therapy relapse of PTEN-deficient prostate cancers While organ-confined PCa is mostly therapeutically manageable, metastatic progression of PCa remains an unmet clinical challenge. Resistance to anoikis, a form of cell death initiated by cell detachment from the surrounding extracellular matrix, is one of the cellular processes critical for PCa progression towards aggressive disease. Therefore, further understanding of anoikis regulation in PCa might provide therapeutic opportunities. Here, we discover that PCa tumors with concomitantly compromised function of two tumor suppressor phosphatases, PP2A and PTEN, are particularly aggressive, having less than 50% 5-year secondary-therapy free patient survival. Functionally, overexpression of PME-1, a PP2A inhibitor protein, inhibits anoikis in PTEN-deficient PCa cells. In vivo, PME-1 inhibition increased apoptosis in in ovo PCa tumor xenografts, and attenuated PCa cell survival in zebrafish circulation. Molecularly, PME-1 deficient PCa cells display increased trimethylation at lysines 9 and 27 of histone H3 (H3K9me3 and H3K27me3), a phenotype corresponding to increased apoptosis sensitivity. In summary, we discover that PME-1 overexpression supports anoikis resistance in PTEN-deficient PCa cells. Clinically, the results identify PME-1 as a candidate biomarker for a subset of particularly aggressive PTEN-deficient PCa. | cancer biology |
A stable pollination environment limits current but not potential evolution of floral traits The vast variation in floral traits at a macroevolutionary level is often interpreted as the result of adaptation to pollinators. However, studies in wild populations often find no evidence of pollinator-mediated selection on flowers. Evolutionary theory predicts this could be the outcome of long periods of stasis under stable conditions, followed by shorter periods of pollinator change that provide selection for innovative phenotypes. We asked if periods of stasis are caused by stabilizing selection, absence of other forms of selection on floral traits, or by low trait ability to respond even if selection is present. We studied Ulex parviflorus, a plant predominantly pollinated by one bee species across its range. We measured heritability and evolvability of floral traits, using genome-wide molecular relatedness in a large wild population, and combined this with estimates of selection on the same individuals. We found evidence for both stabilizing selection and low trait heritability as explanations for stasis in flowers. The area of the standard petal is under stabilizing selection, but the variability observed in the wild is not heritable. A separate trait, floral weight, in turn presents high heritability, but is not currently under selection. We show how a stable environment can lead to a lack of evolutionary change, yet maintain heritable variation to respond to future selection pressures. | evolutionary biology |
Protein structure without structure determination: direct coupling analysis based on in vitro evolution Protein structure is tightly inter-twined with function according to the laws of evolution. Understanding how structure determines function has been the aim of structural biology for decades. Here, we have wondered instead whether it is possible to exploit the function for which a protein was evolutionary selected to gain information on protein structure and on the landscape explored during the early stages of molecular and natural evolution. To answer to this question, we developed a new methodology, which we named CAMELS (Coupling Analysis by Molecular Evolution Library Sequencing), that is able to obtain the in vitro evolution of a protein from an artificial selection based on function. We were able to observe with CAMELS many features of the TEM-1 beta lactamase local fold exclusively by generating and sequencing large libraries of mutational variants. We demonstrated that we can, whenever a functional phenotypic selection of a protein is available, sketch the structural and evolutionary landscape of a protein without utilizing purified proteins, collecting physical measurements or relying on the pool of natural protein variants. | evolutionary biology |
Variations in Structural MRI Quality Significantly Impact Commonly-Used Measures of Brain Anatomy Subject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across developmental and clinical populations. However, quantification of structural image quality is often limited to proxy or indirect measures gathered from functional scans; this may be missing true differences related to these potential artifacts. In this study, we take advantage of novel informatic tools, the CAT12 toolbox, to more directly measure image quality from T1-weighted images to understand if these measures of image quality: 1) relate to rigorous quality-control checks visually completed by human raters; 2) are associated with sociodemographic variables of interest; 3) influence regional estimates of cortical surface area, cortical thickness, and subcortical volumes from the commonly-used Freesurfer tool suite. We leverage public-access data that includes a community-based sample of children and adolescents, spanning a large age-range (N=388; ages 5-21). Interestingly, even after visually inspecting our data, we find image quality significantly impacts derived cortical surface area, cortical thickness, and subcortical volumes from multiple regions across the brain ([~]23.4% of all areas investigated). We believe these results are important for research groups completing structural MRI studies using Freesurfer or other morphometric tools. As such, future studies should consider using measures of image quality to minimize the influence of this potential confound in group comparisons or studies focused on individual differences. | neuroscience |
Rapid neural representations of personally relevant faces The faces of those most personally relevant to us are our primary source of social information, making their timely perception a priority. Recent research indicates that gender, age and identity of faces can be decoded from EEG/MEG data within 100ms. Yet the time course and neural circuitry involved in representing the personal relevance of faces remain unknown. We applied simultaneous EEG-fMRI to examine neural responses to emotional faces of female participants romantic partners, friends, and a stranger. Combining EEG and fMRI in cross-modal representational similarity analyses, we provide evidence that representations of personal relevance start prior to structural encoding at 100ms, with correlated representations in visual cortex, but also in prefrontal and midline regions involved in value representation, and monitoring and recall of self-relevant information. Our results add to an emerging body of research that suggests that models of face perception need to be updated to account for rapid detection of personal relevance in cortical circuitry beyond the core face processing network. | neuroscience |
Single trial dynamics of attentional intensity in visual area V4 Understanding how activity of visual neurons represents distinct components of attention and their dynamics that account for improved visual performance remains elusive because single-unit experiments have not isolated the intensive aspect of attention from attentional selectivity. We isolated attentional intensity and its single trial dynamics as determined by spatially non-selective attentional performance in an orientation discrimination task while recording from neurons in monkey visual area V4. We found that attentional intensity is a distinct cognitive signal that can be distinguished from spatial selectivity, reward expectations and motor actions. V4 spiking on single trials encodes a combination of sensory and cognitive signals on different time scales. Attentional intensity and the detection of behaviorally relevant sensory signals are well represented, but immediate reward expectation and behavioral choices are poorly represented in V4 spiking. These results provide a detailed representation of perceptual and cognitive signals in V4 that are crucial for attentional performance. | neuroscience |
Quantifying Climatic and Socio-Economic Influences on Urban Malaria in Surat, India: A Modelling Study BackgroundCities are becoming increasingly important habitats for mosquito-borne infections. The pronounced heterogeneity of urban landscapes challenges our understanding of the spatio-temporal dynamics of these diseases, and of the influence of climate and socio-economic factors at different spatial scales. Here, we quantify this joint influence on malaria risk by taking advantage of an extensive dataset in both space and time for reported Plasmodium falciparum cases in the city of Surat, Northwest India.
MethodsWe analyzed 10 years of monthly falciparum cases resolved at three nested spatial resolutions (for 7 zones, 32 units and 478 workers units subdivisions, respectively). With a Bayesian hierarchical mixed model that incorporates effects of population density, poverty, humidity and temperature, we investigate the main drivers of spatio-temporal malaria risk at the intermediate scale of districts. The significance of covariates and the model fit is then examined at lower and higher resolutions.
FindingsThe spatial variation of urban malaria cases is strongly stationary in time, whereby locations exhibiting high and low yearly cases remain largely consistent across years. Local socio-economic variation can be summarized with two main principal components, representing poverty and population density respectively. The model that incorporates these two factors together with local temperature and global relative humidity, best explains monthly malaria patterns at the intermediate resolution. The effects of local temperature and population density remain significant at the finest spatial scale. We further identify the specific areas where such increased resolution improves model fit.
InterpretationMalaria risk patterns within the city are largely driven by fixed spatial structures, highlighting the key role of local climate conditions and social inequality. As a result, malaria elimination efforts in the Indian subcontinent can benefit from identifying, predicting and targeting disease hotspots within cities. Spatio-temporal statistical models for the mesoscale of administrative units can inform control efforts, and be complemented with bespoke plans in the identified areas where finer scale data could be of value.
Research in contextO_ST_ABSEvidence before this studyC_ST_ABSUrban areas have become the new dominant ecosystem around the globe. Developing countries comprise the most urbanized regions of the world, with 80% of their population living in cities and an expected increase to 90% by 2050. The large and heterogeneous environments of today challenge the understanding and control of infectious disease dynamics, including of those transmitted by vectors. Malaria in the Indian subcontinent has an important urban component given the existence of a truly urban mosquito vector Anopheles stephensi. A literature search in Mendeley of "urban malaria" and "India" returned 161 publications, in their majority on diagnostics or brief reports on the disease, and on cross-sectional rather than longitudinal studies addressing the spatio-temporal variation of disease risk for a whole city, the subject of our work. A relevant exception is a study for the city of Ahmedabad; this not address multiple seasons across different spatial scales, and climatic conditions are not considered jointly with socio-economic drivers in the modeling. A second Mendeley search on A. stephensi returned 11 publications into two distinct groups: early entomological studies for India and recent reports of the mosquito in the Horn of Africa. This geographical expansion makes the specter of urban malaria a future possibility for the African continent where the disease remains so far rural and peri-urban.
Added value of this studyThis paper relies on an extensive surveillance data set of Plasmodium falciparum cases for Surat (India) to investigate the variation and drivers of malaria risk in an heterogenous urban environment. A statistical model for the spatio-temporal variability of cases is developed, which includes both climatic and socio-economic drivers, with the latter summarized into two major axes of variation. Model fits are compared across three spatial resolutions, ranging from a few zones to a few hundred units. Seasonal hotspots are shown to be largely stationary in time, which allows identification of dominant drivers, including population density and local temperatures, whereas humidity acts globally modulating year-to-year burden. More granular statistical models and datasets like the one analyzed here are needed to capture the effects of socioeconomic and climatic drivers, and to predict current and future malaria incidence patterns within cities.
Implications of all the available evidenceThe analysis identifies relevant resolution which can vary across the city for targeted intervention, including vector control, that would focus on reducing and eliminating transmission hotspots. The modeling framework, incorporating predictors representing climate at local vs. aggregate levels, and major axes of socio-economic variation, should apply to other vector-borne diseases and other cities for which surveillance records are available. The importance of spatially-explicit and sustained surveillance data for informing these models cannot be overstated. | ecology |
Genomic data and multi-species demographic modelling uncover past hybridization between currently allopatric freshwater species Evidence for ancient interspecific gene flow through hybridization has been reported in many animal and plant taxa based on genetic markers. The study of genomic patterns of closely related species with allopatric distributions allow to assess the relative importance of vicariant isolating events and past gene flow. Here, we investigated the role of gene flow in the evolutionary history of four closely related freshwater fish species with currently allopatric distributions in western Iberian rivers - Squalius carolitertii, S. pyrenaicus, S. torgalensis and S. aradensis - using a population genomics dataset of 23 562 SNPs from 48 individuals, obtained through genotyping by sequencing (GBS). We uncovered a species tree with two well differentiated clades: (i) S. carolitertii and S. pyrenaicus; and (ii) S. torgalensis and S. aradensis. By using D-statistics and demographic modelling based on the site frequency spectrum, comparing alternative demographic scenarios of hybrid origin, secondary contact and isolation, we found that the S. pyrenaicus North lineage is likely the result of an ancient hybridization event between S. carolitertii (contributing ~84%) and S. pyrenaicus South lineage (contributing ~16%), consistent with a hybrid speciation scenario. Furthermore, in the hybrid lineage we identify outlier loci potentially affected by selection favouring genes from each parental lineage at different genomic regions. Our results suggest that ancient hybridization can affect speciation and that freshwater fish species currently in allopatry are useful to study these processes. | evolutionary biology |
Effective clustering for single cell sequencing cancer data Single cell sequencing (SCS) technologies provide a level of resolution that makes it indispensable for inferring from a sequenced tumor, evolutionary trees or phylogenies representing an accumulation of cancerous mutations. A drawback of SCS is elevated false negative and missing value rates, resulting in a large space of possible solutions, which in turn makes it difficult, sometimes infeasible using current approaches and tools. One possible solution is to reduce the size of an SCS instance -- usually represented as a matrix of presence, absence, and uncertainty of the mutations found in the different sequenced cells -- and to infer the tree from this reduced-size instance. In this work, we present a new clustering procedure aimed at clustering such categorical vector, or matrix data -- here representing SCS instances, called celluloid. We show that celluloid clusters mutations with high precision: never pairing too many mutations that are unrelated in the ground truth, but also obtains accurate results in terms of the phylogeny inferred downstream from the reduced instance produced by this method. We demonstrate the usefulness of a clustering step by applying the entire pipeline (clustering + inference method) to a real dataset, showing a significant reduction in the runtime, raising considerably the upper bound on the size of SCS instances which can be solved in practice. Our approach, celluloid: clustering single cell sequencing data around centroids is available at https://github.com/AlgoLab/celluloid/ under an MIT license, as well as on the Python Package Index (PyPI) at https://pypi.org/project/celluloid-clust/ | cancer biology |
Global mammalian zooregions reveal a signal of past human impacts Ecologists have long documented that the worlds biota is spatially organized in regions with boundaries shaped by processes acting on geological and evolutionary timescales. Although growing evidence suggests that human impact has been key in how biodiversity is currently assembled, its role as a driver of the geographical organization of biodiversity remains unclear. Here, we quantify the relative importance of human land use from [~]5000 years ago to predict the current assemblage of terrestrial mammals in biogeographical regions across the Earth. Results show that past anthropogenic land use has left an imprint on the taxonomic differentiation of some of the largest biogeographical realms, whereas land use at present stands out as a driver of the taxonomic differences between medium-sized subregions, i.e., within and among continents. Our findings highlight the far-reaching effect that past anthropogenic actions have had on the organization of biodiversity globally. | ecology |
Recovery of trait heritability from whole genome sequence data Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be largely recovered from whole-genome sequence (WGS) data on 25,465 unrelated individuals of European ancestry. We assigned 33.7 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned genetic variance accordingly. The estimated heritability was 0.68 (SE 0.10) for height and 0.30 (SE 0.10) for BMI, with a range of ~0.60 - 0.71 for height and ~0.25 - 0.35 for BMI, depending on quality control and analysis strategies. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection thereon. Cumulatively variants with 0.0001 < MAF < 0.1 explained 0.47 (SE 0.07) and 0.30 (SE 0.10) of heritability for height and BMI, respectively. Our results imply that rare variants, in particular those in regions of low LD, is a major source of the still missing heritability of complex traits and disease. | genetics |
The PIWI/piRNA response is relaxed in a rodent that lacks mobilizing transposable elements Transposable elements (TEs) are genomic parasites that can propagate by inserting copies of themselves into host genomes. Mammalian genomes are typically dominated by LINE retrotransposons and their associated SINEs, and their mobilization in the germline is a challenge to genome integrity. There are genomic defenses against TE proliferation and the PIWI/piRNA defense is among the most well understood. However, the PIWI/piRNA system has been investigated largely in animals with abundant and actively mobilizing TEs and it is unclear how the PIWI/piRNA system functions in the absence of mobilizing TEs. The 13-lined ground squirrel provides an excellent opportunity to examine PIWI/piRNA and TE dynamics within the context of minimal, and possibly nonexistent, TE accumulation. We sequenced RNA and small RNAs pools from the testes of juvenile and adult squirrels and compared results to TE and PIWI/piRNA dynamics in the European rabbit and house mouse. Interestingly in squirrels, despite a lack of young insertions, TEs were still actively transcribed at higher levels compared to mouse and rabbit. All three PIWI proteins were either not expressed, or only minimally expressed, prior to P8 in squirrel testis, but there was little TE expression change with the onset of PIWI expression. We found PIWIs largely did not reduce TE transcription, and the ping-pong cycle was significantly reduced among squirrel LINEs and SINEs compared to the mouse and rabbit. We speculate that, although the PIWI/piRNA system is adaptable to novel TE threats, transcripts from TEs that are no longer threatening receive less attention from PIWI proteins. | evolutionary biology |
Mammalian mitochondrial mutational spectrum as a hallmark of cellular and organismal aging. Mutational spectrum of the mitochondrial genome (mtDNA) does not resemble signatures of any known mutagens and variation in mtDNA mutational spectra between different tissues and organisms is still incomprehensible. Since mitochondria is tightly involved in aerobic energy production, it is expected that mtDNA mutational spectra may be affected by the oxidative damage which is increasing with cellular and organismal aging. However, the well-documented mutational signature of the oxidative damage, G>T substitutions, is typical only for the nuclear genome while it is extremely rare and age-independent in mtDNA. Thus it is still unclear if there is a mitochondria - specific mutational signature of the oxidative damage. Here, reconstructing mtDNA mutational spectra for human cancers originated from 21 tissues with various cell turnover rate, human oocytes fertilized at different ages, and 424 mammalian species with variable generation length which is a proxy for oocyte age, we observed that the frequency of AH>GH substitutions (H - heavy chain notation) is positively correlated with cellular and organismal longevity. Moreover, this mutational bias from AH to GH affects nucleotide content at the fourfold degenerative synonymous positions leading to a deficit of AH and excess of GH, which is especially pronounced in long-lived mammals. Taking into account additionally, that AH>GH is sensitive to time being single stranded during mtDNA asynchronous replication and A>G is associated with oxidative damage of single-stranded DNA in recent bacterial experiments we propose that AH>GH is a mutational signature of oxidative damage in mtDNA. | genomics |
Familiar neighbours, but not relatives, enhance fitness in a territorial mammal SummaryOne of the outstanding questions in evolutionary biology is the extent to which mutually beneficial interactions and kin-selection can facilitate the evolution of cooperation by mitigating conflict between interacting organisms. The indirect fitness benefits gained from associating with kin are an important pathway to conflict resolution [1], but conflict can also be resolved if individuals gain direct benefits from cooperating with one another (e.g. mutualism or reciprocity) [2]. Owing to the kin-structured nature of many animal societies, it has been difficult for previous research to assess the relative importance of these mechanisms [3-5]. However, one area that might allow for the relative roles of kin-selection and mutualistic benefits to be disentangled is in the resolution of conflict over territorial space [6]. While much research has focused on group-living species, the question of how cooperation can first be favoured in solitary, territorial species remains a key question. Using 22 years of data from a population of North American red squirrels, we assessed how kinship and familiarity with neighbours affected fitness in a territorial mammal. While living near kin did not enhance fitness, familiarity with neighbours increased survival and annual reproductive success. These fitness benefits were strong enough to compensate for the effects of aging later in life, with potential consequences for the evolution of senescence. We suggest that such substantial fitness benefits provide the opportunity for the evolution of cooperation between adversarial neighbours, offering insight into the role that mutually beneficial behaviours might play in facilitating and stabilizing social systems.
Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY | evolutionary biology |
The degree of polymerization and sulfation patterns in heparan sulfate are critical determinants of cytomegalovirus entry into host cells Several enveloped viruses, including herpesviruses attach to host cells by initially interacting with cell surface heparan sulfate (HS) proteoglycans followed by specific coreceptor engagement which culminates in virus-host membrane fusion and virus entry. Interfering with HS-herpesvirus interactions has long been known to result in significant reduction in virus infectivity indicating that HS play important roles in initiating virus entry. In this study, we provide a series of evidence to prove that specific sulfations as well as the degree of polymerization (dp) of HS govern human cytomegalovirus (CMV) binding and infection. First, purified CMV extracellular virions preferentially bind to sulfated longer chain HS on a glycoarray compared to a variety of unsulfated glycosaminoglycans including unsulfated shorter chain HS. Second, the fraction of glycosaminoglycans (GAG) displaying higher dp and sulfation has a larger impact on CMV titers compared to other fractions. Third, cell lines deficient in specific glucosaminyl sulfotransferases produce significantly reduced CMV titers compared to wild-type cells and virus entry is compromised in these mutant cells. Finally, cells pretreated with a peptide that specifically binds sulfated-HS produce significantly reduced virus titers compared to the control peptide treated cells. Taken together, these results highlight the significance of HS chain length and sulfation patterns in CMV attachment and infectivity.
IMPORTANCEHeparan sulfate (HS) is a linear polysaccharide found in all animal tissues. It binds to a variety of protein ligands, including cytokines, chemokines, growth factors and morphogens and regulates a wide range of biological activities, including developmental processes, angiogenesis, blood coagulation, and tumor metastasis. The molecular diversity in HS chains generates unique binding sites for specific ligands and can offer preferential binding for a specific virus over other viruses or cellular ligands. In the current study human cytomegalovirus (CMV) was found to bind preferentially to uniquely sulfated and polymerized HS. The HS mimics designed with these properties inhibited CMV infection. The results were corroborated by parallel studies in mutant mouse cells as well as using peptide inhibition. Combined together, the data suggests that CMV preferentially attaches to uniquely modified HS and thus this virus-host interaction is amenable to targeting by specifically designed HS mimics or peptides. | microbiology |
Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a polymerase chain reaction (PCR) step (Nextera), and two were PCR-free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, we assessed two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80{degrees}C). All DNA isolations were performed in duplicate, totaling 80 samples excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generate comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously.
ImportancePrevious research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories. | microbiology |
Phylogenetic inference of changes in amino acid propensities with single-position resolution Fitness conferred by the same allele may differ between genotypes, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence alignments statistically, but the existing methods are data-intensive and aggregate multiple sites. Here, we develop an approach to detect individual amino acids that confer different fitness in different groups of species from combined sequence and phylogenetic data. Using the fact that the probability of a substitution to an amino acid depends on its fitness, our method looks for amino acids such that substitutions to them occur more frequently in one group of lineages than in another. We validate our method using simulated evolution of a protein site under different scenarios and show that it has high specificity for a wide range of assumptions regarding the underlying changes in selection, while its sensitivity differs between scenarios. We apply our method to the env gene of two HIV-1 subtypes, A and B, and to the HA gene of two influenza A subtypes, H1 and H3, and show that the inferred fitness changes are consistent with the fitness differences observed in deep mutational scanning experiments. We find that changes in relative fitness of different amino acid variants within a site do not always trigger episodes of positive selection and therefore may not result in an overall increase in the frequency of substitutions, but can still be detected from changes in relative frequencies of different substitutions.
Author summaryWhich amino acids are acceptable at a certain protein site can change with time. In viruses, for example, this can be due to changes in mechanisms of drug resistance and immune escape in the course of evolution. Here, we develop a method for detecting such changes from how evolutionary events are distributed over an evolutionary tree. Informally, we infer that a certain amino acid is favored in a certain group of lineages if substitutions giving rise to it repeatedly occur in the evolution of this group, and disfavored if such substitutions are rare. In surface proteins of HIV-1 and influenza A, we find that changes in preferences detected with d-test match those observed in deep mutational scanning experiments. Our purely bioinformatic approach allows inference of changes in selection between lineages from sequences alone, shedding light on the functional differences between strains or species even in the absence of any structural or functional data. | evolutionary biology |
Extensive genetic mixing within the clam genus Corbicula AO_SCPLOWBSTRACTC_SCPLOW"Occasional" sexuality occurs when a species combines clonal reproduction and genetic mixing. This strategy is predicted to combine the advantages of both asexuality and sexuality, but its actual consequences on the genetic diversity and species longevity are poorly understood. Androgenesis, a reproductive mode in which the offspring inherits its entire nuclear genome from the father, is often reported as a strictly clonal reproductive mode. Androgenesis is the predominant reproductive mode within the hermaphroditic, invasive lineages of the mollusk genus Corbicula. Their ability to reproduce clonally through androgenesis has been determinant in their invasive success, having colonized during the 20th century American and European freshwater systems, where they became notorious invaders with a widespread, global distribution. However, in androgenetic Corbicula clams, occasional genetic mixing between distinct lineages has also been observed when the sperm of one lineage fertilizes the oocyte of another one. Because of these occasional introgressions, the genetic relationships between Corbicula species remained unclear, and the biogeographic origins of the invasive androgenetic lineages have been challenging to identify. To address these issues, we analyzed the patterns of allele sharing for several nuclear and mitochondrial molecular markers among Corbicula individuals collected across both the native and invasive range. Our results show the occurrence of an allelic pool encompassing all Corbicula freshwater species worldwide, including sexual and androgenetic ones, which highlights the substantial genetic mixing within this genus. However, the differences in allele sharing patterns between invasive lineages, and the low diversity within each lineage, suggest recent, distinct biogeographic origins of invasive Corbicula androgenetic lineages. Finally, the polyploidy, high heterozygosity, and hybrid phenotypes and genotypes found in our study probably originated from hybridization events following egg parasitism between distinct Corbicula lineages. This extensive cross-lineage mixing found in Corbicula may generate nuclear diversity in an otherwise asexually reproducing species. | evolutionary biology |
Rate-limiting transport of positive charges through the Sec-machinery is integral to the mechanism of protein transport Transport of proteins across and into membranes is a fundamental biological process with the vast majority being conducted by the ubiquitous Sec machinery. In bacteria, this is usually achieved when the SecY-complex engages the cytosolic ATPase SecA (secretion) or translating ribosomes (insertion). Great strides have been made towards understanding the mechanism of protein translocation. Yet, important questions remain - notably, the nature of the individual steps that constitute transport, and how the proton-motive force (PMF) across the plasma membrane contributes. Here, we apply a recently developed high-resolution protein transport assay to explore these questions. We find that pre-protein transport is limited primarily by the diffusion of arginine residues across the membrane, particularly in the context of bulky hydrophobic sequences. This specific effect of arginine, caused by its positive charge, is mitigated for lysine which can be deprotonated and transported across the membrane in its neutral form. These observations have interesting implications for the mechanism of protein secretion, suggesting a simple mechanism by which PMF can aid transport, and enabling a proton ratchet, wherein re-protonation of exiting lysine residues prevents channel re-entry, biasing transport in the outward direction. | biochemistry |
Single cell transcriptomics identifies master regulators of dysfunctional pathways in SOD1 ALS motor neurons BackgroundBulk RNA-Seq has been extensively utilized to investigate the molecular changes accompanying motor neuron degeneration in Amyotrophic Lateral Sclerosis (ALS). However, due to the heterogeneity and degenerating phenotype of the neurons, it has proved difficult to assign specific changes to neuronal subtypes and identify which factors drive these changes. Consequently, we have utilized single cell transcriptomics of degenerating motor neurons derived from ALS patients to uncover key transcriptional drivers of dysfunctional pathways.
ResultsSingle cell analysis of spinal neuronal cultures derived from SOD1 E100G ALS and isogenic iPSCs allowed us to classify cells into neural subtypes including motor neurons and interneurons. Differential expression analysis between disease and control motor neurons revealed downregulation of genes involved in synaptic structure, neuronal cytoskeleton, mitochondrial function and autophagy. Interestingly, interneurons did not show similar suppression of these homeostatic functions. Single cell expression data enabled us to derive a context-specific transcriptional network relevant to ALS neurons. Master regulator analysis based on this network identified core transcriptional factors driving the ALS MN gene dysregulation. Specifically, we identified activation of SMAD2, a downstream mediator of the TGF-{beta} signalling pathway as a potential driving factor of ALS motor neuron degeneration. Our phenotypic analysis further confirmed that an activated TGF-{beta} signalling is major driver of motor neuron loss in SOD1 ALS. Importantly, expression analysis of TGF{beta} target genes and computational analysis of publicly available datasets indicates that activation of TGF{beta} signalling may be a common mechanism shared between SOD1, FUS and sporadic ALS.
ConclusionsOur results demonstrate the utility of single cell transcriptomics in mapping disease-relevant gene regulatory networks driving neurodegeneration in ALS motor neurons. We find that ALS-associated mutant SOD1 targets transcriptional networks that perturb motor neuron homeostasis. | genomics |
Population receptive fields of human primary visual cortex organised as DC-balanced bandpass filters. The response to visual stimulation of population receptive fields (pRF) in the human visual cortex can be accurately modelled with a Difference of Gaussians model, yet many aspects of their organisation remain poorly understood. Here, we examined the theoretical underpinnings of this model and argue that the DC-balanced Difference of Gaussians (DoG) holds a number of advantages over a DC-biased DoG. Through functional magnetic resonance imaging (fMRI) pRF mapping, we compared performance of DC-balanced and DC-biased models in human primary visual cortex and found that when model complexity is taken into account, the DC-balanced model is preferred. Finally, we present evidence indicating that the BOLD signal DC-offset contains information related to the processing of visual stimuli. Taken together, the results indicate that V1 neurons are at least frequently organised in the exact constellation that allows them to function as bandpass-filters, which allows for the separation of stimulus contrast and luminance. We further speculate that if the DoG models stimulus contrast, the DC-offset may reflect stimulus luminance. These findings suggest that it may be possible to separate contrast and luminance processing in fMRI experiments and this could lead to new insights on the haemodynamic response. | neuroscience |
CRISPR-SID: identifying EZH2 as a druggable target for desmoid tumors via in vivo dependency mapping Cancer precision medicine implies identification of tumor-specific vulnerabilities associated with defined oncogenic pathways. Desmoid tumors are soft-tissue neoplasms strictly driven by Wnt signaling network hyperactivation. Despite this clearly defined genetic etiology and the strict and unique implication of the Wnt/{beta}-catenin pathway, no specific molecular targets for these tumors have been identified. To address this caveat, we developed fast and semi-high throughput genetic Xenopus tropicalis desmoid tumor models to identify and characterize novel drug targets. We used multiplexed CRISPR/Cas9 genome editing in these models to simultaneously target a tumor suppressor gene (apc) and candidate dependency genes. Our methodology CRISPR/Cas9 Selection mediated Identification of Dependencies (CRISPR-SID) uses calculated deviations between experimentally observed gene editing outcomes and deep-learning-predicted double strand break repair patterns, to identify genes under negative selection during tumorigenesis. This revealed EZH2 and SUZ12, both encoding polycomb repressive complex 2 components, and the transcription factor CREB3L1, as genetic dependencies for desmoid tumors. In vivo EZH2 inhibition by Tazemetostat induced partial regression of established autochthonous tumors. In vitro models of patient desmoid tumor cells revealed a direct effect of Tazemetostat on Wnt pathway activity. CRISPR-SID represents a potent novel approach for in vivo mapping of tumor vulnerabilities and drug target identification.
Significance StatementCRISPR-SID was established in the diploid frog Xenopus tropicalis for in vivo elucidation of cancer cell vulnerabilities. CRISPR-SID uses deep learning predictions and binomial theory to identify genes under positive or negative selection during autochthonous tumor development. Using CRISPR-SID in a genetic model for desmoid tumors, treatment-recalcitrant mesenchymal tumors driven by hyper-activation of the Wnt signaling pathway, we identified EZH2 and SUZ12, both encoding critical components of the polycomb repressive complex 2, as dependency genes for desmoid. Finally, we demonstrate the promise of EZH2 inhibition as a novel therapeutic strategy for desmoid tumors. With the simplicity of CRISPR sgRNA multiplexing in Xenopus embryos the CRISPR-SID method may be applicable to reveal vulnerabilities in other tumor types. | cancer biology |
OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions Chromatin accessibility, as a powerful marker of active DNA regulatory elements, provides valuable information for understanding regulatory mechanisms. The revolution in high-throughput methods has accumulated massive chromatin accessibility profiles in public repositories. Nevertheless, utilization of these data is hampered by cumbersome collection, time-consuming processing, and manual chromatin accessibility (openness) annotation of genomic regions. To fill this gap, we developed OpenAnnotate (http://health.tsinghua.edu.cn/openannotate/) as the first web server for efficiently annotating openness of massive genomic regions across various biosample types, tissues, and biological systems. In addition to the annotation resource from 2729 comprehensive profiles of 614 biosample types of human and mouse, OpenAnnotate provides user-friendly functionalities, ultra-efficient calculation, real-time browsing, intuitive visualization, and elaborate application notebooks. We show its unique advantages compared to existing databases and toolkits by effectively revealing cell type-specificity, identifying regulatory elements and 3D chromatin contacts, deciphering gene functional relationships, inferring functions of transcription factors, and unprecedentedly promoting single-cell data analyses. We anticipate OpenAnnotate will provide a promising avenue for researchers to construct a more holistic perspective to understand regulatory mechanisms. | bioinformatics |
Rapid label-free identification of pathogenic bacteria species from a minute quantity 1 exploiting three-dimensional quantitative phase imaging and artificial neural network The healthcare industry is in dire need for rapid microbial identification techniques. Microbial infection is a major healthcare issue with significant prevalence and mortality, which can be treated effectively during the early stages using appropriate antibiotics. However, determining the appropriate antibiotics for the treatment of the early stages of infection remains a challenge, mainly due to the lack of rapid microbial identification techniques. Conventional culture-based identification and matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy are the gold standard methods, but the sample amplification process is extremely time-consuming. Here, we propose an identification framework that can be used to measure minute quantities of microbes by incorporating artificial neural networks with three-dimensional quantitative phase imaging. We aimed to accurately identify the species of bacterial bloodstream infection pathogens based on a single colony-forming unit of the bacteria. The successful distinction between a total of 19 species, with the accuracy of 99.9% when ten bacteria were measured, suggests that our framework can serve as an effective advisory tool for clinicians during the initial antibiotic prescription.
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[email protected]@8b4eb4org.highwire.dtl.DTLVardef@1dc2452org.highwire.dtl.DTLVardef@1d4888c_HPS_FORMAT_FIGEXP M_FIG C_FIG | microbiology |
Quality control of large genome datasets using genome fingerprints The 1000 Genomes Project (TGP) is a foundational resource which serves the biomedical community as a standard reference cohort for human genetic variation. There are now seven public versions of these genomes. The TGP Consortium produced the first by mapping its final data release against human reference sequence GRCh37, then "lifted over these genomes to the improved reference sequence (GRCh38) when it was released, and remapped the original data to GRCh38 with two similar pipelines. As best practice quality validation, the pipelines that generated these versions were benchmarked against the Genome In A Bottle Consortiums platinum quality genome (NA12878). The New York Genome Center recently released the results of independently resequencing the cohort at greater depth (30X), a phased version informed by the inclusion of related individuals, and independently remapped the original variant calls to GRCh38. We evaluated all seven versions using genome fingerprinting, which supports ultrafast genome comparison even across reference versions. We noted multiple issues including discrepancies in cohort membership, disagreement on the overall level of variation, evidence of substandard pipeline performance on specific genomes and in specific regions of the genome, cryptic relationships between individuals, inconsistent phasing, and annotation distortions caused by the history of the reference genome itself. We therefore recommend global quality assessment by rapid genome comparisons, using genome fingerprints and other metrics, alongside benchmarking as part of best practice quality assessment of large genome datasets. Our observations also help inform the decision of which version to use, to support analyses by individual researchers. | genomics |
Tumor-targeted delivery of childhood vaccine recall antigens by attenuated Listeria reduces pancreatic cancer Pancreatic ductal adenocarcinoma is highly metastatic, poorly immunogenic, and immune suppression prevents T cell activation in the tumor microenvironment. We developed a microbial-based immunotherapeutic concept for selective delivery of a highly immunogenic tetanus toxoid protein (TT856-1313), into tumor cells by attenuated Listeria monocytogenes, and reactivation of pre-existing TT-specific memory T cells (generated during childhood) to kill infected tumor cells. Thus, TT here functions as an alternative for neoantigens. Treatment of KPC mice with Listeria-TT resulted in TT accumulation in tumors and inside tumor cells, and attraction of predominantly TT-specific memory CD4 T cells. Moreover, gemcitabine (GEM) combined with Listeria-TT significantly improved the migration of CD4 T cells into tumors and the production of perforin and granzyme B, turning cold tumors into immunological hot tumors. In vivo depletion of T cells in Listeria-TT+GEM-treated mice demonstrated CD4 T cell-mediated eradication of tumors and metastases (Mann-Whitney p<0.05). In addition, peritumoral lymph node like structures (LNS) were observed in close contact with the pancreatic tumors displaying CD4 T cells and CD8 T cells of KPC mice treated with Listeria-TT or Listeria-TT+GEM. The production of perforin and granzyme B was observed in LNS of KPC mice that received Listeria-TT+GEM. This combination not only reduced tumor burden (80%) and metastases (87%) significantly (p<0.05, Mann-Whitney), but also improved the survival time of KPC mice with advanced pancreatic cancer substantially (Mantel-Cox p<0.0001). Our results unveil new mechanisms of Listeria and GEM improving immunotherapy for PDAC. | immunology |
Heterologous Cas9 and non-homologous end joining as a Potentially Organism-Agnostic Knockout (POAK) system in bacteria Making targeted gene deletions is essential for studying organisms, but is difficult in many prokaryotes due to the inefficiency of homologous recombination based methods. Here, I describe an easily modifiable, single-plasmid system that can be used to make rapid, sequence targeted, markerless knockouts in both a Gram-negative and a Gram-positive organism. The system is comprised of targeted DNA cleavage by Cas9 and error-prone repair by Non-Homologous End Joining (NHEJ) proteins. I confirm previous results showing that Cas9 and NHEJ can make knockouts when NHEJ is expressed before Cas9. Then, I show that Cas9 and NHEJ can be used to make knockouts when expressed simultaneously. I term the new method Potentially Organism-Agnostic Knockout (POAK) system and characterize its function in Escherichia coli and Weissella confusa. First, I develop a novel transformation protocol for W. confusa. Next, I show that, as in E. coli, POAK can create knockouts in W. confusa. Characterization of knockout efficiency across galK in both E. coli and W. confusa showed that while all gRNAs are effective in E. coli, only some gRNAs are effective in W. confusa, and cut site position within a gene does not determine knockout efficiency for either organism. I examine the sequences of knockouts in both organisms and show that POAK produces similar edits in both E. coli and W. confusa. Finally, as an example of the importance of being able to make knockouts quickly, I target W. confusa sugar metabolism genes to show that two sugar importers are not necessary for metabolism of their respective sugars. Having demonstrated that simultaneous expression of Cas9 and NHEJ is sufficient for making knockouts in two minimally related bacteria, POAK represents a hopeful avenue for making knockouts in other under-utilized bacteria. | synthetic biology |
Heterochromatin renewal after release from growth arrest controls genome-wide transcription re-activation in S.cerevisiae The budding yeast SIR complex (Silent Information Regulator) is the principal actor in heterochromatin formation, which causes epigenetically regulated gene silencing phenotypes. The dynamics of the SIR complex during the cell cycle are however not well understood. It is consequently still not known how the SIR complex is maintained and/or restored after genome replication and cell division, and how the underlying silenced state is transmitted form one cell generation to the next. We used the tag switch RITE system to measure genome wide turnover rates of the SIR subunit Sir3p during and after exit from growth arrest caused by nutrient depletion. Our results show that Sir3p subunits have high rates of exchange immediately after release from growth arrest. "Maternal" Sir3p is consequently almost completely replaced with newly synthesized Sir3p in subtelomeric regions by the end of the first cell cycle after release from growth arrest. The sudden increase in the off rate of Sir3 upon release from growth arrest leads to SIR complex instability that is exacerbated in strains with sub optimal amounts of newly synthesized Sir3p. Unexpectedly, heightened SIR complex instability in these Sir3p "hypo-morphs" has global effects on gene expression with faster reactivation of hundreds of euchromatic genes upon exit from growth arrest. | molecular biology |
MetaNovo: a probabilistic approach to peptide discovery in complex mass spectrometry datasets BackgroundMicrobiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focussed search libraries based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing will only target the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. We describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored databases for target-decoy searches directly at the proteome level, enabling analyses without prior expectation of sample composition or metagenomic data generation, and compatible with standard downstream analysis pipelines.
ResultsWe compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome database - but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying a known sample contaminant without prior expectation.
ConclusionsBy estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence search databases. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself. The pipeline source code is available on GitHub1 and documentation is provided to run the software as a singularity-compatible docker image available from the Docker Hub2. | bioinformatics |
An Integrated Platform for High-Throughput Nanoscopy Diffraction-unlimited single-molecule techniques like STORM and (F)PALM enable three-dimensional (3D) fluorescence imaging at tens of nanometer resolution and are invaluable to investigate sub-cellular organization. The multitude of camera frames required to reconstruct a super-resolved image limits the typical throughput of these techniques to tens of cells per day, rendering these methods incompatible with large-scale cell biological or clinical application. STORM acquisition rates can be increased by over an order of magnitude, however the data volumes of about 40 TB a day and concomitant analysis burdens exceed the capacity of existing workflows. Here we present an integrated platform which transforms SMLM from a trick-pony technique into a work horse for cell biology. We leverage our developments in microscopy-specific data compression, distributed storage, and distributed analysis to automatically perform real-time localization analysis, which enable SMLM at throughputs of 10,000 cells a day. We implemented these advances in a fully-integrated environment that supports a highly-flexible architecture for distributed analysis, enabling quickly- and graphically-reconfigurable analyses to be automatically initiated from the microscope during acquisition, remotely executed, and even feedback and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, the PYthon-Microscopy Environment (PYME), is easily configurable for hardware control on custom microscopes, and includes a plugin framework so users can readily extend all components of their imaging, visualization, and analysis pipeline. PYME is cross-platform, open source, and efficiently puts high-caliber visualization and analysis tools into the hands of both microscope developers and users. | biophysics |
Inter-subunit coupling enables fast CO2-fixation by reductive carboxylases Enoyl-CoA carboxylases/reductases (ECRs) belong to the most efficient CO2-fixing enzymes described to date. However, the molecular mechanisms underlying ECRs extraordinary catalytic activity on the level of the protein assembly remain elusive. Here we used a combination of ambient temperature X-ray Free Electron Laser (XFEL) and cryogenic synchrotron experiments to study the structural organization of the ECR from Kitasatospora setae. K. setae ECR is a homo-tetramer that differentiates into a dimer of dimers of open- and closed-form subunits in the catalytically active state. Using molecular dynamics simulations and structure-based mutagenesis, we show that catalysis is synchronized in K. setae ECR across the pair of two dimers. This conformational coupling of catalytic domains is conferred by individual amino acids to achieve high CO2-fixation rates. Our results provide unprecedented insights into the dynamic organization and synchronized inter- and intra-subunit communications of this remarkably efficient CO2-fixing enzyme during catalysis.
Significance StatementFixation of CO2 offers real potential for reaching negative CO2 emissions in bioenergy, and bioproduct utilization. The capture and conversion of atmospheric CO2 remains a challenging task. Existing biological systems can be exploited and optimized for this use. Bacterial enoyl-CoA carboxylases/reductases (ECRs) encompass the fastest CO2-fixing enzymes found in nature to date. However, the mechanisms underlying ECRs extraordinary catalytic activity remain elusive. Our structural, computational, and biochemical results elucidate the dynamic structural organization of the ECR complex and describe how coupled motions of catalytic domains in the ECR tetramer drive carboxylation. This mechanistic understanding is critical for engineering highly efficient CO2-fixing biocatalysts for bioenergy and bioproduct applications. | biophysics |
Network science inspires novel tree shape statistics 1The shape of phylogenetic trees can be used to gain evolutionary insights. A trees shape specifies the connectivity of a tree, while its branch lengths reflect either the time or genetic distance between branching events; well-known measures of tree shape include the Colless and Sackin imbalance, which describe the asymmetry of a tree. In other contexts, network science has become an important paradigm for describing structural features of networks and using them to understand complex systems, ranging from protein interactions to social systems. Network science is thus a potential source of many novel ways to characterize tree shape, as trees are also networks. Here, we tailor tools from network science, including diameter, average path length, and betweenness, closeness, and eigenvector centrality, to summarize phylogenetic tree shapes. We thereby propose tree shape summaries that are complementary to both asymmetry and the frequencies of small configurations. These new statistics can be computed in linear time and scale well to describe the shapes of large trees. We apply these statistics, alongside some conventional tree statistics, to phylogenetic trees from three very different viruses (HIV, dengue fever and measles), from the same virus in different epidemiological scenarios (influenza A and HIV) and from simulation models known to produce trees with different shapes. Using mutual information and supervised learning algorithms, we find that the statistics adapted from network science perform as well as or better than conventional statistics. We describe their distributions and prove some basic results about their extreme values in a tree. We conclude that network science-based tree shape summaries are a promising addition to the toolkit of tree shape features. All our shape summaries, as well as functions to select the most discriminating ones for two sets of trees, are freely available as an R package at http://github.com/Leonardini/treeCentrality. | bioinformatics |
A suite of rare microbes interacts with a dominant, heritable, fungal endophyte to influence plant trait expression Endophytes are microbes that live, for at least a portion of their life history, within plant tissues. Endophyte assemblages are often composed of a few abundant taxa and many infrequently-observed, rare taxa. The ways in which most endophytes affect host phenotype are unknown; however, certain dominant endophytes can influence plants in ecologically meaningful ways-including by affecting growth and contributing to immune responses. In contrast, the effects of rare endophytes have been unexplored, and how rare and common endophytes might interact is also unknown. Here, we manipulate both the suite of rare foliar endophytes (including both fungi and bacteria) and Alternaria fulva-a dominant, vertically- transmitted fungus-within the fabaceous forb Astragalus lentiginosus. We report that rare, low-biomass endophytes affected host size and foliar %N, but only when the dominant fungal endophyte (A. fulva) was not present. A. fulva also reduced plant size and %N, but these deleterious effects on the host could be offset by a striking antagonism we observed between this heritable fungus and a foliar pathogen. These results are unusual in that they are derived from experimental manipulation in a non-crop or non-grass system and demonstrate that interactions among taxa determine the net effect of endophytic assemblages on their hosts. We suggest that the myriad infrequently-observed endophytes within plant leaves may be more than a collection of uninfluential, commensal organisms, but instead have meaningful ecological roles. | ecology |
Stabilising effects of competition and diversity determine vaccine impact on antibiotic resistance evolution Bacterial vaccines can protect recipients from contracting potentially antibiotic-resistant infections. But by altering the selective balance between sensitive and resistant strains, vaccines may also suppress--or spread--antibiotic resistance among unvaccinated individuals. Predicting the outcome requires knowing what drives selection for resistance in bacterial pathogens, and in particular, what maintains the circulation of both antibiotic-sensitive and resistant strains of bacteria. Using mathematical modelling, we show that the frequency of penicillin resistance in Streptococcus pneumoniae (pneumococcus) across 27 European countries can be explained by between-host diversity in antibiotic use, heritable diversity in pneumococcal carriage duration, or frequency-dependent selection brought about by within-host competition between resistant and sensitive strains. We use our calibrated models to predict the impact of non-serotype-specific pneumococcal vaccination upon the prevalence of carriage, incidence of disease, and frequency of resistance for S. pneumoniae. We find that the relative strength and directionality of competition between resistant and sensitive pneumococcal strains is the most important determinant of whether vaccination promotes, inhibits, or has little effect upon the evolution of antibiotic resistance. Finally, we show that country-specific differences in pathogen transmission substantially alter the predicted impact of vaccination, highlighting that policies for managing resistance with vaccines must be tailored to a specific pathogen and setting.
One sentence summaryFrequency-dependent competition and extrinsically-maintained diversity shape selection for antibiotic resistance following vaccination. | evolutionary biology |
Reward motivation increases univariate activity but has limited effect on coding of task-relevant information across the frontoparietal cortex Selection and integration of information based on current goals is fundamental for goal-directed behavior. Reward motivation has been shown to improve behavioral performance, yet the neural mechanisms that link motivation and control processes, and in particular its effect on context-dependent information processing, remain unclear. We used functional magnetic resonance imaging (fMRI) in 24 human volunteers (13 females) to test whether reward motivation enhances the coding of task-relevant information across the frontoparietal cortex, as would be predicted based on previous experimental evidence and theoretical accounts. In a cued target detection task, participants detected whether an object from a cued visual category was present in a subsequent display. The combination of the cue and the object visual category determined the behavioral status of the objects. To manipulate reward motivation, half of all trials offered the possibility of a monetary reward. We observed an increase with reward in overall univariate activity across the frontoparietal control network when the cue and subsequent object were presented. Multivariate pattern analysis (MVPA) showed that behavioral status information for the objects was conveyed across the network. However, in contrast to our prediction, reward did not increase the discrimination between behavioral status conditions in the stimulus epoch of a trial when object information was processed depending on a current context. In the high-level general-object visual region, the lateral occipital complex, the representation of behavioral status was driven by visual differences and was not modulated by reward. Our study provides useful evidence for the limited effects of reward motivation on task-related neural representations and highlights the necessity to unravel the diverse forms and extent of these effects. | neuroscience |
Reference plasmid pHXB2_D is an HIV-1 molecular clone that exhibits identical LTRs and a single integration site indicative of an HIV provirus ObjectiveTo compare long-read nanopore DNA sequencing (DNA-seq) with short-read sequencing-by-synthesis for sequencing a full-length (e.g., non-deletion, nor reporter) HIV-1 model provirus in plasmid pHXB2_D.
DesignWe sequenced pHXB2_D and a control plasmid pNL4-3_gag-pol({Delta}1443-4553)_EGFP with long- and short-read DNA-seq, evaluating sample variability with resequencing (sequencing and mapping to reference HXB2) and de novo viral genome assembly.
MethodsWe prepared pHXB2_D and pNL4-3_gag-pol({Delta}1443-4553)_EGFP for long-read nanopore DNA-seq, varying DNA polymerases Taq (Sigma-Aldrich) and Long Amplicon (LA) Taq (Takara). Nanopore basecallers were compared. After aligning reads to the reference HXB2 to evaluate sample coverage, we looked for variants. We next assembled reads into contigs, followed by finishing and polishing. We hired an external core to sequence-verify pHXB2_D and pNL4-3_gag-pol({Delta}1443-4553)_EGFP with single-end 150 base-long Illumina reads, after masking sample identity.
ResultsWe achieved full-coverage (100%) of HXB2 HIV-1 from 5 to 3 long terminal repeats (LTRs), with median per-base coverage of over 9000x in one experiment on a single MinION flow cell. The longest HIV-spanning read to-date was generated, at a length of 11,487 bases, which included full-length HIV-1 and plasmid backbone with flanking host sequences supporting a single HXB2 integration event. We discovered 20 single nucleotide variants in pHXB2_D compared to reference, verified by short-read DNA sequencing. There were no variants detected in the HIV-1 segments of pNL4-3_gag-pol({Delta}1443-4553)_EGFP.
ConclusionsNanopore sequencing performed as-expected, phasing LTRs, and even covering full-length HIV. The discovery of variants in a reference plasmid demonstrates the need for sequence verification moving forward, in line with calls from funding agencies for reagent verification. These results illustrate the utility of long-read DNA-seq to advance the study of HIV at single integration site resolution. | genomics |
Coupling Metastasis to pH-Sensing GPR68 Using a Novel Small Molecule Inhibitor An acidic milieu is a hallmark of the glycolytic metabolism that occurs in cancerous cells. The acidic environment is known to promote cancer progression, but the underlying signaling and cell biological underpinnings of these phenomena are not well understood. Here, we describe ogremorphin, a first-in-class small-molecule inhibitor of GPR68, an extracellular proton-sensing and mechanosensing G protein-coupled receptor. Ogremorphin was discovered in a chemical genetic zebrafish screen for its ability to perturb neural crest development, which shares basic cell behaviors of migration and invasion with cancer metastasis. Ogremorphin also inhibited migration and invasive behavior of neural crest-derived human melanoma cells in vitro. Furthermore, in phenome-wide association studies (PheWAS), we identified an aberrantly activated variant of GPR68, which is associated with cancer metastasis in vivo and promotes invasive phenotypes of cancer cells in vitro. Thus, extracellular proton-sensing GPR68 signaling promotes cell migration and invasion during embryonic development and may do likewise in cancer progression. | cancer biology |
Untangling the Indonesian tangle net fishery: describing a data-poor fishery targeting large threatened rays (Order Batoidea) O_LIShark-like rays (Order Rhinopristiformes) are among the most threatened families of marine fish. Yet little is known about their populations, as these rays are normally taken as opportunistic catch in fisheries targeting other species and are thus poorly reported. One exception is the Indonesian tangle net fishery, which targets shark-like rays.
C_LIO_LIMarket surveys of Muara Angke landing site in Jakarta, north-western Java (including one frozen shipment from Benoa Harbour, Bali), were conducted between 2001 and 2005, and recorded landed catch for this fishery. Recent catch data from Indonesian Capture Fisheries (2017 - 2018) were also examined to provide contemporary information about landed catch.
C_LIO_LI1,559 elasmobranchs (sharks and rays) were recorded, comprised of 24 species of rays and nine species of sharks. The most abundant species landed were the pink whipray Pateobatis fai and the bottlenose wedgefish Rhynchobatus australiae, the latter being the main target species.
C_LIO_LICatch composition varied based on differences in species catchability and may also be indicative of localized declines. The fishery was highly selective for larger sized individuals, however smaller size classes of target species were also caught in other Indonesian fisheries resulting in fishing pressure across all age classes.
C_LIO_LIEvidence of substantial declines in global landings of wedgefish species, and the observed shift in catch composition in the Indonesian tangle net fishery, increases concerns about the status of shark-like rays and stingrays in Indonesia.
C_LI | zoology |
On the efficacy of restoration in stream networks: comments, critiques, and prospective recommendations Swan and Brown (2017) recently addressed the effects of restoration on stream communities under the meta-community framework. Using a combination of headwater and mainstem streams, Swan and Brown (2017) evaluated how position within a stream network affected the outcome of restoration on invertebrate communities. Ostensibly, their hypotheses were partially supported as restoration had stronger effects in headwater streams: invertebrate taxonomic richness was increased and temporal variability decreased in restored reaches; however, these results were not consistent upon closer scrutiny for both the original paper (Swan and Brown 2017) and the later erratum (Swan and Brown 2018). Here, I provide a secondary analysis of the data, with hypotheses and interpretations in the context of stream, meta-community, and restoration ecology. Swan and Brown (2017, 2018) evaluated the effect of restoration on sites receiving various combinations of in-channel manipulation and riparian reforestation treatments. Given the difference in the relative importance of environmental filtering and dispersal between headwaters and mainstems and the structure of river networks, I contend that different restoration treatments have differential effects between headwaters and mainstems. I hypothesized in-channel manipulations would have more consistent effects between headwaters and mainstems compared to riparian reforestation, and I used this hypothesis to guide site selection in the re-analysis. I then compared results from the re-analysis to those presented by Swan and Brown (2017, 2018). I did not find any effects of restoration on local diversity, spatial dissimilarity, or temporal variability, let alone differential effects of restoration between headwaters and mainstems; these results are contrary Swan and Brown (2017, 2018), who reported that restoration increased taxonomic richness, increased spatial dissimilarity, and decreased temporal variability in restored headwater streams. I demonstrate further that the statistical tests conducted by Swan and Brown (2017, 2018) were invalid and, therefore, recommend the use of the results presented here. More broadly, I suggest, in agreement with Swan and Brown (2017, 2018) and a growing body of research, that river and stream restoration will likely have greater success if a regional approach is taken to designing and implementing restoration projects. | ecology |
Integrase-mediated differentiation circuits improve evolutionary stability of burdensome and toxic functions in E. coli Advances in synthetic biology, bioengineering, and computation allow us to rapidly and reliably program cells with increasingly complex and useful functions. However, because the functions we engineer cells to perform are typically unnecessary for cellular survival and burdensome to cell growth, they can be rapidly lost due to the processes of mutation and natural selection. To improve the evolutionary stability of engineered functions in a general manner, we developed an integrase-recombination-based differentiation gene circuit in Escherichia coli. In this system, differentiated cells uniquely carry out burdensome or toxic engineered functions but have limited capacity to grow (terminal differentiation), preventing the propagation of selectively advantageous loss of function mutations that inevitably arise. To experimentally implement terminal differentiation, we co-opted the R6K plasmid system, using differentiation to simultaneously activate T7 RNAP-driven expression of arbitrary engineered functions, and inactivate expression of {pi} protein (an essential factor for R6K plasmid replication), thereby allowing limitation of differentiated cell growth through antibiotic selection. We experimentally demonstrate terminal differentiation increases both duration and magnitude of high-burden T7 RNAP-driven expression, and that its evolutionary stability can be further improved with strategic redundancy. Using burdensome overexpression of a fluorescent protein as a model engineered function, our terminal differentiation circuit results in a ~2.8-fold (single-cassette) and ~4.2-fold (two-cassette) increase of total fluorescent protein produced compared to high-burden naive expression in which all cells inducibly express T7 RNAP. Finally, we demonstrate that differentiation can enable the expression of even toxic functions, a feat not achieved to our knowledge by any other strategy for addressing long-term evolutionary stability. Overall, this study provides an effective generalizable strategy for protecting engineered functions from evolutionary degradation. | synthetic biology |
Regulatory network-based imputation of dropouts in single-cell RNA sequencing data Single-cell RNA sequencing (scRNA-seq) methods are typically unable to quantify the expression levels of all genes in a cell, creating a need for the computational prediction of missing values ( dropout imputation). Most existing dropout imputation methods are limited in the sense that they exclusively use the scRNA-seq dataset at hand and do not exploit external gene-gene relationship information. Further, it is unknown if all genes equally benefit from imputation or which imputation method works best for a given gene.
Here, we show that a transcriptional regulatory network learned from external, independent gene expression data improves dropout imputation. Using a variety of human scRNA-seq datasets we demonstrate that our network-based approach outperforms published state-of-the-art methods. The network-based approach performs particularly well for lowly expressed genes, including cell-type-specific transcriptional regulators. Further, the cell-to-cell variation of 12.6% to 48.2% of the genes could not be adequately imputed by any of the methods that we tested. In those cases gene expression levels were best predicted by the mean expression across all cells, i.e. assuming no measurable expression variation between cells. These findings suggest that different imputation methods are optimal for different genes. We thus implemented an R-package called ADImpute (available via Bioconductor https://bioconductor.org/packages/release/bioc/html/ADImpute.html) that automatically determines the best imputation method for each gene in a dataset.
Our work represents a paradigm shift by demonstrating that there is no single best imputation method. Instead, we propose that imputation should maximally exploit external information and be adapted to gene-specific features, such as expression level and expression variation across cells.
Author summarySingle-cell RNA-sequencing (scRNA-seq) allows for gene expression to be quantified in individual cells and thus plays a critical role in revealing differences between cells within tissues and characterizing them in healthy and pathological conditions. Because scRNA-seq captures the RNA content of individual cells, lowly expressed genes, for which few RNA molecules are present in the cell, are easily missed. These events are called dropouts and considerably hinder analysis of the resulting data. In this work, we propose to make use of gene-gene relationships, learnt from external and more complete datasets, to estimate the true expression of genes that could not be quantified in a given cell. We show that this approach generally outperforms previously published methods, but also that different genes are better estimated with different methods. To allow the community to use our proposed method and combine it with existing ones, we created the R package ADImpute, available through Bioconductor. | bioinformatics |
Resistance to aztreonam in combination with non-β-lactam β-lactamase inhibitors due to the layering of mechanisms in Escherichia coli identified following mixed culture selection. Using mixed culture selection, we show how reduced envelope permeability, reduced target-site affinity, and increased {beta}-lactamase production layer to confer aztreonam/{beta}-lactamase inhibitor resistance in Escherichia coli. We report a clinical isolate producing CTX-M-15 and CMY-4, lacking OmpF, and carrying a PBP3 mutation. It is resistant to aztreonam plus the inhibitors avibactam, relebactam and vaborbactam. Mobilisation of blaSHV-12 into this isolate generated a derivative additionally resistant to aztreonam plus the bicyclic boronate inhibitors 2 and taniborbactam. | microbiology |
Attention Decorrelates Sensory and Motor Signals in the Mouse Visual Cortex Visually-guided behaviors depend on the activity of cortical networks receiving visual inputs and transforming these signals to guide appropriate actions. However, non-retinal inputs, carrying motor signals as well as cognitive and attentional modulatory signals, also activate these cortical regions. How these networks avoid interference between coincident signals ensuring reliable visual behaviors is poorly understood. Here, we observed neural responses in the dorsal-parietal cortex of mice during a visual discrimination task driven by visual stimuli and movements. We found that visual and motor signals interacted according to two canonical mechanisms: divisive normalization and response demixing. Interactions were contextually modulated by the animals state of attention, with attention amplifying visual and motor signals and decorrelating them in a low-dimensional space of neural activations. These findings reveal canonical computational principles operating in dorsal-parietal networks that enable separation of incoming signals for reliable visually-guided behaviors during interactions with the environment. | neuroscience |
A developmental framework linking neurogenesis and circuit formation in the Drosophila CNS The mechanisms specifying neuronal diversity are well-characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, we mapped the developmental origin of 160 interneurons from seven bilateral neural progenitors (neuroblasts), and identify them in a synapse-scale TEM reconstruction of the Drosophila larval CNS. We find that lineages concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, we show that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, we demonstrate that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system. | neuroscience |
Fitness-related traits are maximized in recently introduced, slow-growing populations of an invasive clam: is this a response to strong r-selection? Many species are shifting their ranges being forced to rapidly respond to novel stressful environmental conditions. Colonizing individuals experience strong selective forces that favor the expression of life history traits notably affecting dispersal and reproductive rates in newly invaded habitats. Limited information is currently available on trait variation within the invasive range despite being critical for understanding ecological and evolutionary factors that drive the process of range expansion of invasive species. Here we evaluated life history shifts of the widely introduced Asian clam Corbicula, within its invaded range. Through an exhaustive literature search, we obtained data for 17 invasive Corbicula populations from different ecosystems worldwide. We tested the relationship between population and individual parameters relevant to the process of range expansion. Our main results are that recently introduced Corbicula populations were characterized by (i) low density and low rate of population increase, (ii) clams reproduced earlier in slow-growing populations, and (iii) density had no effect on population increase. All Corbicula populations analyzed in this study, which are fixed for one genotype (lineage Form A/R), experienced different selective environments in the introduced range. These findings support the perspective that adaptive phenotypic plasticity favored the expression of traits that maximize fitness in recently established populations, which faced stronger r-selective forces relative to long-established ones. We discuss the role of plasticity in facilitating rapid adaptation and increasing the likelihood of populations to overcome difficulties associated with low densities and low population increase in newly invaded areas. | ecology |
O-glycosylation regulates plant developmental transitions downstream of miR156 The timing of plant developmental transitions is decisive for reproductive success and thus tightly regulated. The transition from juvenile to adult vegetative and later to the reproductive phase is controlled by an endogenous pathway regulated by miR156, targeting the SQUAMOSA PROMOTER BINDING PROTEIN (SBP/SPL) family of transcription factors. SPLs regulate a number of developmental processes, such as trichome formation, leaf shape and floral transition. Such complex regulatory pathways often involve post-translational modifications (PTMs), integrating a range of internal and external signals. One of these PTMs is O-glycosylation, the attachment of a single monosaccharide to serine or threonine of nuclear and cytoplasmic proteins, which is found on a number of very diverse proteins. O-GlcNAcylation is the most common type of cytosolic O-glycosylation, but in plants also O-fucose modification occurs. Here we show that mutants defective in the O-fucosyltransferase SPINDLY (SPY) show accelerated developmental transitions. Genetic analysis shows that this effect is independent of miR156 levels, but partly dependent on functional SPLs. In a phenotyping analysis, we found that SPY and SPLs also control leaf growth, as loss of function mutants showed defects in cell expansion, while SPL9 also regulates cell division in rosette leaves. Moreover, SPLs interact directly with SPY and are O-glycosylated. Our results show that O-glycosylation is involved at several steps in the regulation of developmental transitions and organ growth in Arabidopsis thaliana. | plant biology |
An Optimized Registration Workflow and Standard Geometric Space for Small Animal Brain Imaging The reliability of scientific results critically depends on reproducible and transparent data processing. Cross-subject and cross-study comparability of imaging data in general, and magnetic resonance imaging (MRI) data in particular, is contingent on the quality of registration to a standard reference space. In small animal MRI this is not adequately provided by currently used processing workflows, which utilize high-level scripts optimized for human data, and adapt animal data to fit the scripts, rather than vice-versa. In this fully reproducible article we showcase a generic workflow optimized for the mouse brain, alongside a standard reference space suited to harmonize data between analysis and operation. We introduce four separate metrics for automated quality control (QC), and a visualization method to aid operator inspection. Benchmarking this workflow against common legacy practices reveals that it performs more consistently, better preserves variance across subjects while minimizing variance across sessions, and improves both volume and smoothness conservation RMSE approximately 2-fold. We propose this open source workflow and the QC metrics as a new standard for small animal MRI registration, ensuring workflow robustness, data comparability, and region assignment validity, all of which are indispensable prerequisites for the comparability of scientific results across experiments and centers. | neuroscience |
Uncovering the effects of Müllerian mimicry on the evolution of conspicuousness in colour patterns Variation in the conspicuousness of colour patterns is observed within and among defended prey species. The evolution of conspicuous colour pattern in defended species can be strongly impaired because of increased detectability by predators. Nevertheless, such evolution of the colour pattern can be favoured if changes in conspicuousness result in Mullerian mimicry with other defended prey. Here, we develop a model describing the population dynamics of a conspicuous defended prey species, and we assess the invasion conditions of derived phenotypes that differ from the ancestral phenotype by their conspicuousness. Such change in conspicuousness may then modify their level of mimicry with the local community of defended species. Derived colour pattern displayed in this focal population can therefore be either exactly similar, partially resembling or completely dissimilar to the local mimicry ring displaying the ancestral colour pattern. We assume that predation risk depends (1) on the number of individuals sharing a given colour pattern within the population, (2) on the occurrence of co-mimetic defended species, and (3) on the availability of alternative edible prey. Using a combination of analytical derivations and numerical simulations, we show that less conspicuous colour patterns are generally favoured within mimicry rings, unless reduced conspicuousness impairs mimicry. By contrast, when a mutation affecting the colour pattern leads to a shift toward a better protected mimicry ring, crypsis is no longer necessarily beneficial and a more conspicuous colour pattern can be favoured. The selected aposematic pattern then depends on the local composition of mimetic communities, as well as on the detectability, memorability and level of mimicry of the colour patterns. | evolutionary biology |
On the cortical mapping function -- visual space, cortical space, and crowding The retino-cortical visual pathway is retinotopically organized: Neighbourhood relationships on the retina are preserved in the mapping to the cortex. Size relationships in that mapping are also highly regular: The size of a patch in the visual field that maps onto a cortical patch of fixed size follows, along any radius and in a wide range, simply a linear function with retinal eccentricity. As a consequence, and under simplifying assumptions, the mapping of retinal to cortical locations follows a logarithmic function along that radius. While this has already been shown by Fischer (1973), the link between the linear function - which describes the local behaviour by the cortical magnification factor M - and the logarithmic location function for the global behaviour, has never been made fully explicit. The present paper provides such a link as a set of ready-to-use equations using Levi and Kleins E2 nomenclature, and examples for their validity and applicability in the retinotopic mapping literature are discussed. The equations allow estimating M in the retinotopic centre and values thus derived from the literature are provided. A new structural parameter, d2, is proposed to characterize the cortical map, as a cortical counterpart to E2, and typical values for it are given. One pitfall is discussed and spelt out as a set of equations, namely the common myth that a pure logarithmic function will give an adequate map: The popular omission of a constant term renders the equations ill defined in, and around, the retinotopic centre. The correct equations are finally extended to describe the cortical map of Boumas law on visual crowding. The result contradicts recent suggestions that critical crowding distance corresponds to a constant cortical distance. | neuroscience |
Memory for Individual Items is Related to Non-Reinforced Preference Change It is commonly assumed that memories contribute to value-based decisions. Nevertheless, most theories of value-based decision-making do not account for memory influences on choice. Recently, new interest has emerged in the interactions between these two fundamental processes, mainly using reinforcement-based paradigms. Here, we aimed to study the role memory processes play in preference change following the non-reinforced cue-approach training (CAT) paradigm. In CAT, the mere association of cued items with a speeded motor response influences choices. Previous studies with this paradigm showed that a single training session induces a long-lasting effect of enhanced preferences for high-value trained stimuli, that is maintained for several months. We hypothesized that CAT influences memory accessibility for trained items, leading to enhanced accessibility of their positive associative memories and in turn to preference changes. In two pre-registered experiments, we tested whether memory for trained items was enhanced following CAT, in the short and in the long-term, and whether memory modifications were related to choices. We found that memory was enhanced for trained items and that better memory was correlated with enhanced preferences at the individual item level, both immediately and one month following CAT. Our findings show that memory plays a central role in value-based decision-making following CAT, even in the absence of external reinforcements. These findings contribute to new theories relating memory and value-based decision-making and set the groundwork for the implementation of novel behavioral interventions that lead to long-lasting behavioral change. | neuroscience |
Predation strategies of the bacterium Bdellovibrio bacteriovorus result in overexploitation and bottlenecks With increasing antimicrobial resistance, alternatives for treating infections or removing resistant bacteria are urgently needed, such as the bacterial predator Bdellovibrio bacteriovorus or bacteriophage. Therefore, we need to better understand microbial predator-prey dynamics. We developed mass-action mathematical models of predation for chemostats, which capture the low substrate concentration and slow growth typical for intended application areas of the predators such as wastewater treatment, aquaculture or the gut. Our model predicted that predator survival required a minimal prey size, explaining why Bdellovibrio is much smaller than its prey. A too good predator (attack rate too high, mortality too low) overexploited its prey leading to extinction (tragedy of the commons). Surprisingly, a predator taking longer to produce more offspring outcompeted a predator producing fewer offspring more rapidly (rate versus yield trade-off). Predation was only efficient in a narrow region around optimal parameters. Moreover, extreme oscillations under a wide range of conditions led to severe bottlenecks. A bacteriophage outcompeted Bdellovibrio due to its higher burst size and faster life cycle. Together, results suggest that Bdellovibrio would struggle to survive on a single prey, explaining why it must be a generalist predator and suggesting it is better suited than phage to environments with multiple prey.
ImportanceThe discovery of antibiotics led to a dramatic drop in deaths due to infectious disease. Increasing levels of antimicrobial resistance, however, threaten to reverse this progress. There is thus a need for alternatives, such as therapies based on phage and predatory bacteria that kill bacteria regardless of whether they are pathogens or resistant to antibiotics. To best exploit them, we need to better understand what determines their effectiveness. By using a mathematical model to study bacterial predation in realistic slow growth conditions, we found that the generalist predator Bdellovibrio is most effective within a narrow range of conditions for each prey. For example, a minimum prey size is required, and the predator should not be too good as this would result in over-exploitation risking extinction. Together these findings give insights into the ecology of microbial predation and help explain why Bdellovibrio needs to be a generalist predator. | microbiology |
In the absence of reproductive isolation - Extensive gene flow after speciation In the conventional view, species are separate gene pools delineated by reproductive isolation (RI). However, species may also be delineated by merely a small set of "speciation genes" without full RI. It is thus important to know whether "good species" (defined by the "secondary sympatry" test) do continue to exchange genes. Here, we carry out sequencing and de novo high-quality assembly of the genomes of two closely related mangrove species (Rhizophora mucronata and R. stylosa). Whole-genome re-sequencing of individuals across their range on the tropical coasts shows their genomes to be well delineated in allopatry. They became sympatric in northeastern Australia but remain distinct species in contact. Nevertheless, their genomes harbor [~] 4,000 to 10,000 introgression blocks, each averaging only about 3-4 Kb. These fine-grained introgressions indicate that gene flow has continued long after speciation. Non-introgressable "genomic islets," averaging only 1.4 Kb, may contribute to speciation as they often harbor diverging genes underlying flower development and gamete production. In conclusion, RI needs not be the main criterion of species delineation even though all species would eventually be fully reproductively isolated. | evolutionary biology |
tRNAscan-SE 2.0: Improved Detection and Functional Classification of Transfer RNA Genes tRNAscan-SE has been widely used for transfer RNA (tRNA) gene prediction for over twenty years, developed just as the first genomes were decoded. With the massive increase in quantity and phylogenetic diversity of genomes, the accurate detection and functional prediction of tRNAs has become more challenging. Utilizing a vastly larger training set, we created nearly one hundred specialized isotype-and clade-specific models, greatly improving tRNAscan-SEs ability to identify and classify both typical and atypical tRNAs. We employ a new comparative multi-model strategy where predicted tRNAs are scored against a full set of isotype-specific covariance models, allowing functional prediction based on both the anticodon and the highest-scoring isotype model. Comparative model scoring has also enhanced the programs ability to detect tRNA-derived SINEs and other likely pseudogenes. For the first time, tRNAscan-SE also includes fast and highly accurate detection of mitochondrial tRNAs using newly developed models. Overall, tRNA detection sensitivity and specificity is improved for all isotypes, particularly those utilizing specialized models for selenocysteine and the three subtypes of tRNA genes encoding a CAU anticodon. These enhancements will provide researchers with more accurate and detailed tRNA annotation for a wider variety of tRNAs, and may direct attention to tRNAs with novel traits. | bioinformatics |
The neuronal calcium sensor Synaptotagmin-1 and SNARE proteins cooperate to dilate fusion pores All membrane fusion reactions proceed through an initial fusion pore, including calcium-triggered release of neurotransmitters and hormones. Expansion of this small pore to release cargo is energetically costly and regulated by cells, but the mechanisms are poorly understood. Here we show that the neuronal/exocytic calcium sensor Synaptotagmin-1 (Syt1) promotes expansion of fusion pores induced by SNARE proteins. Pore dilation relied on calcium-induced insertion of the tandem C2 domain hydrophobic loops of Syt1 into the membrane, previously shown to reorient the C2 domain. Mathematical modelling suggests that C2B reorientation rotates a bound SNARE complex so that it exerts force on the membranes in a mechanical lever action that increases the height of the fusion pore, provoking pore dilation to offset the bending energy penalty. We conclude that Syt1 exerts novel non-local calcium-dependent mechanical forces on fusion pores that dilate pores and assist neurotransmitter and hormone release.
SIGNIFICANCE STATEMENTDuring neurotransmitter release, calcium-induced membrane insertion of the C2B domain of Synaptotagmin re-orients the bound SNARE complex which dilates the fusion pore in a mechanical lever action. | biophysics |
Low centrosome numbers correlate with higher aggressivity in ovarian cancer Centrosome amplification, the presence of more than two centrosomes in a cell is a common feature of most human cancer cell lines. However, little is known about centrosome numbers of human cancers and whether amplification or other numerical aberrations are frequently present. To address this question, we have analyzed a large cohort of human epithelial ovarian cancers (EOCs) from 100 patients. Using state-of-the-art microscopy, we have determined the Centrosome-Nucleus Index (CNI) of each tumor. We found that EOCs show infrequent centrosome amplifications. Strikingly, the large majority of these tumors presented low CNIs. We show that low CNI tumors are enriched in the mesenchymal subgroup and correlate with poor patient survival. Our findings highlight a novel paradigm linking low centrosome number with highly aggressive behavior in ovarian cancers and show that the CNI signature may be used to stratify ovarian cancers. | cancer biology |
Protein and Lipid Mass Concentration Measurement in Tissues by Stimulated Raman Scattering Microscopy Cell mass and its chemical composition are important aggregate cellular variables for physiological processes including growth control and tissue homeostasis. Despite their central importance, it has been difficult to quantitatively measure these quantities from single cells in intact tissue. Here, we introduce Normalized Raman Imaging (NoRI), a Stimulated Raman Scattering (SRS) microscopy method that provides the local concentrations of protein, lipid and water from live or fixed tissue samples with high spatial resolution. Using NoRI, we demonstrate that single cell protein, lipid and water concentrations are maintained in a tight range in cells under same physiological conditions and are altered in different physiological states such as cell cycle stages, attachment to substrates of different stiffness, or by entering senescence. In animal tissues, protein and lipid concentration varies with cell types, yet an unexpected cell-to-cell heterogeneity was found in cerebellar Purkinje cells. Protein and lipid concentration profile provides a new means to quantitatively compare disease-related pathology as demonstrated using models of Alzheimers disease. Our demonstration shows that NoRI is a broadly applicable tool for probing the biological regulation of protein mass, lipid mass and water in cellular and tissue growth, homeostasis, and disease. | bioengineering |
Cholinergic modulation of dentate gyrus processing through dynamic reconfiguration of inhibitory circuits The dentate gyrus (DG) of the hippocampus plays a key role in memory formation and it is known to be modulated by septal projections. By performing electrophysiology and optogenetics we evaluated the role of cholinergic modulation in the processing of afferent inputs in the DG. We showed that mature granule cells (GCs), but not adult-born immature neurons, have increased responses to afferent perforant path stimuli upon cholinergic modulation. This is due to a highly precise reconfiguration of inhibitory circuits, differentially affecting Parvalbumin and Somatostatin interneurons, resulting in a nicotinic-dependent perisomatic disinhibition of GCs. This circuit reorganization provides a mechanism by which mature GCs could escape the strong inhibition they receive, creating a window of opportunity for plasticity. Indeed, coincident activation of perforant path inputs with optogenetic release of acetylcholine produced a long-term potentiated response in GCs, essential for memory formation. | neuroscience |
Estimation of biodiversity metrics by environmental DNA metabarcoding compared with visual and capture surveys of river fish communities O_LIInformation on alpha (local), beta (between habitats), and gamma (regional) diversity is fundamental to understanding biodiversity as well as the function and stability of community dynamics. Methods like environmental DNA (eDNA) metabarcoding are currently considered useful to investigate biodiversity.
C_LIO_LIWe compared the performance of eDNA metabarcoding with visual and capture surveys for estimating alpha and gamma diversity of river fish communities, and nestedness and turnover in particular.
C_LIO_LIIn five rivers across west Japan, by comparison to visual/capture surveys, eDNA metabarcoding detected more species in the study sites (i.e., alpha diversity). Consequently the overall number of species in the region (i.e., gamma diversity) was higher. In particular, the species found by visual/capture surveys were encompassed by those detected by eDNA metabarcoding.
C_LIO_LIEstimates of community diversity within rivers differed between survey methods. Although we found that the methods show similar levels of community nestedness and turnover within the rivers, visual/capture surveys showed more distinct community differences from upstream to downstream. Our results suggest that eDNA metabarcoding may be a suitable method for community assemblage analysis, especially for understanding regional community patterns, for fish monitoring in rivers.
C_LI | ecology |
Complex community-wide consequences of consumer sexual dimorphism Sexual dimorphism is a ubiquitous source of within-species variation, yet the communitylevel consequences of sex differences remain poorly understood. Here, we analyze a bitrophic model of two competing resource species and a sexually-reproducing consumer species. We show that consumer sex differences in resource acquisition can have striking consequences for consumer-resource coexistence, abundance, and dynamics. Under both direct interspecific competition and apparent competition between two resource species, sexual dimorphism in consumers attack rates can mediate coexistence of the resource species, while in other cases can lead to exclusion when stable coexistence is typically expected. Slight sex differences in total resource acquisition also can reverse competitive outcomes and lead to density cycles. These effects are expected whenever both consumer sexes require different amounts or types of resources to reproduce. Our results suggest that consumer sexual dimorphism, which is common, has wide-reaching implications for the assembly and dynamics of natural communities.
Statement of authorshipDB SD and SJS designed the study, SJS performed the mathematical analysis, SD performed the simulations and drafted the manuscript. All authors revised the manuscript.
Data accessibility statementNo data is used | ecology |
The regenerating skeletal muscle niche guides muscle stem cell self-renewal Skeletal muscle stem cells (MuSCs) are essential for muscle regeneration and maintenance. While MuSCs typically are quiescent and reside in an asymmetric niche between the basal lamina and myofiber membrane: to repair or maintain muscle, MuSCs activate, proliferate and differentiate to repair injured tissue, and self-renew to replenish MuSCs. Little is known about the timing of MuSC self-renewal during muscle regeneration and the cellular processes that direct MuSC self-renewal fate decisions. Using DNA-based lineage tracing, we find that during muscle regeneration most MuSCs self-renew from 5-7 days post-injury, following fusion of myogenic cells to regenerate myofibers. Single cell sequencing of the myogenic cells in regenerating muscle reveals that non-cell autonomous signaling networks regulate MuSC self-renewal allowing identification of asymmetrically distributed proteins in self-renewing MuSCs. Cell transplantation experiments verified that the regenerating environment signals MuSC self-renewal. Our results define the critical window for MuSC self-renewal emphasizing the temporal contribution of the regenerative muscle environment on MuSC fate, establishing a new paradigm for restoring the MuSC pool during muscle regeneration. | cell biology |
Synthetic design of farnesyl-electrostatic peptides for development of a protein kinase A membrane translocation switch Molecular switches that respond to a biochemical stimulus in cells have proven utility as a foundation for developing molecular sensors and actuators that could be used to address important biological questions. Developing a molecular switch unfortunately remains difficult as it requires elaborate coordination of sensing and actuation mechanisms built into a single molecule. Here, we rationally designed a molecular switch that changes its subcellular localization in response to an intended stimulus such as an activator of protein kinase A (PKA). By arranging the sequence for Kemptide in tandem, we designed a farnesylated peptide whose localization can dramatically change upon phosphorylation by PKA. After testing a different valence number of Kemptide as well as modulating the linker sequence connecting them, we identified an efficient peptide switch that exhibited dynamic translocation between plasma membranes and internal endomembranes in a PKA activity dependent manner. Due to the modular design and small size, our PKA switch can have versatile utility in future studies as a platform for visualizing and perturbing signal transduction pathways, as well as for performing synthetic operations in cells. | cell biology |
First report of marine sponge Chelonaplysilla delicata (Demospongiae: Darwinellidae) from the Andaman Sea/Indian Ocean with a baseline information of epifauna on a mesophotic shipwreck During a biodiversity assessment on a wreck located in the Andaman Sea (Andaman Islands), a single specimen of sponge Chelonaplysilla delicata was recorded. Our finding confirms the species taxonomy and highlights the current observation as a first report from the Andaman Sea/ Indian Ocean. The baseline information of epifauna is further stated in this study. | ecology |
Quantitative analysis of ZFY and CTCF reveals dependent recognition of tandem zinc finger proteins. The human genome contains around 800 C2H2 Zinc Finger Proteins (ZFPs), and many of them are composed of long tandem arrays of zinc fingers. Current motif prediction models assume longer finger arrays correspond to longer DNA-binding motifs and higher specificity. However, recent experimental efforts to identify ZFP binding sites in vivo contradict this assumption, with many having short motifs. Here, we systematically test how multiple zinc fingers contribute to binding for three model ZFPs: Zinc Finger Y (ZFY), CTCF, and ZNF343. Using ZFY, which contains 13 fingers, we quantitatively characterize its binding specificity with several methods, including Affinity-seq, HT-SELEX, Spec-seq and fluorescence anisotropy, and find evidence for dependent recognition where downstream fingers can recognize some extended motifs only in the presence of an intact core site. For the genomic insulator CTCF, additional high-throughput affinity measurements reveal that its upstream specificity profile depends on the strength of the core, violating presumed additivity and positionindependence. Moreover, the effect of different epigenetic modifications within the core site depends on the strength of flanking upstream site, providing new insight into how the previously identified intellectual disability-causing and cancer-related mutant R567W disrupts upstream recognition and deregulates CTCFs methylation sensitivity. Lastly, we used ZNF343 as example to show that a simple iterative motif analysis strategy based on a small set of prefixed cores can reveal the dependent relationship between cores and upstream motifs. These results establish that the current underestimation of ZFPs motif lengths is due to our lack of understanding of intrinsic properties of tandem zinc finger recognition, including irregular motif structure, variable spacing, and dependent recognition between sub-motifs. These results also motivate a need for better recognition models beyond additive, position-weight matrix to predict ZFP specificities, occupancies, and the molecular mechanisms of disease mutations. | genetics |
Gene-experience correlation during cognitive development: Evidence from the Adolescent Brain Cognitive Development (ABCD) StudySM BackgroundFindings in adults have shown more culturally sensitive crystallized measures of intelligence have greater heritability, these results were not able to be shown in children.
MethodsWith data from 8,518 participants, aged 9 to 11, from the Adolescent Brain Cognitive Development (ABCD) Study(R), we used polygenic predictors of intelligence test performance (based on genome-wide association meta-analyses of data from 269,867 individuals) and of educational attainment (based on data from 1.1 million individuals), associating these predictors with neurocognitive performance. We then assessed the extent of mediation of these associations by a measure of recreational reading.
Resultsmore culturally sensitive crystallized measures were more strongly associated with the polygenic predictors than were less culturally sensitive fluid measures. This mirrored heritability differences reported previously in adults and suggests similar associations in children. Recreational reading more strongly statistically mediated the genetic associations with crystallized than those with fluid measures of cognition.
ConclusionThis is consistent with a prominent role of gene-environment correlation in cognitive development measured by "crystallized" intelligence tests. Such experiential mediators may represent malleable targets for improving cognitive outcomes. | neuroscience |
Role of Water-bridged Interactions in Metal Ion Coupled Protein Allostery Allosteric communication between distant parts of proteins controls many cellular functions, in which metal ions are widely utilized as effectors to trigger the allosteric cascade. Due to the involvement of strong coordination interactions, the energy landscape dictating the metal ion binding is intrinsically rugged. How metal ions achieve fast binding by overcoming the landscape ruggedness and thereby efficiently mediate protein allostery is elusive. By performing molecular dynamics simulations for the Ca2+ binding mediated allostery of the calmodulin (CaM) domains, each containing two Ca2+ binding helix-loop-helix motifs (EF-hands), we revealed the key role of water-bridged interactions in Ca2+ binding and protein allostery. The bridging water molecules between Ca2+ and binding residue reduces the ruggedness of ligand exchange landscape by acting as a lubricant, facilitating the Ca2+ coupled protein allostery.
Calcium-induced rotation of the helices in the EF-hands, with the hydrophobic core serving as the pivot, leads to exposure of hydrophobic sites for target binding. Intriguingly, despite being structurally similar, the response of the two symmetrically arranged EF-hands upon Ca2+ binding is asymmetric. Breakage of symmetry is needed for efficient allosteric communication between the EF-hands. The key roles that water molecules play in driving allosteric transitions are likely to be general in other metal ion mediated protein allostery. | biochemistry |
An automated model reduction tool to guide the design and analysis of synthetic biological circuits We present an automated model reduction algorithm that uses quasi-steady state approximation to minimize the error between the desired outputs. Additionally, the algorithm minimizes the sensitivity of the error with respect to parameters to ensure robust performance of the reduced model in the presence of parametric uncertainties. We develop the theory for this model reduction algorithm and present the implementation of the algorithm that can be used to perform model reduction of given SBML models. To demonstrate the utility of this algorithm, we consider the design of a synthetic biological circuit to control the population density and composition of a consortium consisting of two different cell strains. We show how the model reduction algorithm can be used to guide the design and analysis of this circuit. | synthetic biology |
Metacognitive awareness of difficulty in action selection: the role of the cingulo-opercular network The question whether and how we are able to monitor our own cognitive states (metacognition) has been a matter of debate for decades. Do we have direct access to our cognitive processes or can we only infer them indirectly based on their consequences? In the current study, we wanted to investigate the brain circuits that underlie the metacognitive experience of fluency in action selection. To manipulate action-selection fluency we used a subliminal response priming paradigm. On each trial, both male and female human participants additionally engaged in the metacognitive process of rating how hard they felt it was to respond to the target stimulus. Despite having no conscious awareness of the prime, results showed that participants rated incompatible trials (during which subliminal primes interfered with the required response) to be more difficult than compatible trials (where primes facilitated the required response) reflecting metacognitive awareness of difficulty. This increased sense of subjective difficulty was mirrored by increased activity in the rostral cingulate zone (RCZ) and the anterior insula, two regions that are functionally closely connected. Importantly, this reflected activations that were unique to subjective difficulty ratings and were not explained by reaction times or prime-response compatibility. We interpret these findings in light of a possible grounding of the metacognitive judgement of fluency in action selection in interoceptive signals resulting from increased effort. | neuroscience |
An optimized tissue clearing protocol for rat brain labeling, imaging, and high throughput analysis The advent of whole brain clearing and imaging methods extends the breadth and depth at which brain-wide neural populations and structures can be studied. However, these methods have yet to be applied to larger brains, such as the brains of the common laboratory rat, despite the importance of these models in behavioral neuroscience research. Here we introduce AdipoClear+, an optimized immunolabeling and clearing methodology for application to adult rat brain hemispheres, and validate its application through the testing of common antibodies and electrode tract visualization. In order to extend the accessibility of this methodology for general use, we have developed an open source platform for the registration of rat brain volumes to standard brain atlases for high throughput analysis. | neuroscience |
Increasing plant group productivity through latent genetic variation for cooperation Historic yield advances in the major crops have to a large part been achieved by selection for improved productivity of groups of plant individuals such as high-density stands. Research suggests that such improved group productivity depends on "cooperative" traits (e.g. erect leaves, short stems) that - while beneficial to the group - decrease individual fitness under competition. This poses a problem for some traditional breeding approaches, especially when selection occurs at the level of individuals, because "selfish" traits will be selected for and reduce yields in high-density monocultures. One approach therefore has been to select individuals based on ideotypes with traits expected to promote group productivity. However, this approach is limited to architectural and physiological traits whose effects on growth and competition are relatively easy to anticipate.
Here, we developed a general and simple method for the discovery of alleles promoting cooperation in plant stands. Our method is based on the game-theoretical premise that alleles increasing cooperation incur a cost to the individual but benefit the monoculture group. Testing the approach using the model plant Arabidopsis thaliana, we found a major effect locus where the rarer allele was associated with increased cooperation and productivity in high-density stands. The allele likely affects a pleiotropic gene, since we find that it is also associated with reduced root competition but higher resistance against disease. Thus, even though cooperation is considered evolutionarily unstable, conflicting selective forces acting on a pleiotropic gene might maintain latent genetic variation for it in nature. Such variation, once identified in a crop, could be rapidly leveraged in modern breeding programs and provide efficient routes to increase yields. | plant biology |
Muscle torques provide more sensitive measures of post-stroke movement deficits than joint angles. The whole repertoire of complex human motion is enabled by forces applied by our muscles and controlled by the nervous system. The of stroke on the complex multi-joint motor control is difficult to quantify in a meaningful way that informs about the underlying deficit in the active motor control and intersegmental coordination. We tested the idea that post-stroke deficit can be quantified with high sensitivity using motion capture and inverse modeling of a broad range of reaching movements. Our hypothesis is that muscle moments estimated based on active joint torques provide a more sensitive measure of post-stroke motor deficits than joint angle and angular velocity. The motion of twenty-two participants was captured while performing reaching movements in a center-out task, presented in virtual reality. We used inverse dynamics analysis to derive active joint torques that were the result of muscle contractions, termed muscle torques, that caused the recorded multi-joint motion. We then applied a novel analysis to separate the component of muscle torque related to gravity compensation from that related to intersegmental dynamics. Our results show that individual reaching movements can be characterized with higher information content using muscle torques rather than joint angles. Moreover, muscle torques allow for distinguishing between the individual motor deficits due to aging or stroke from the typical differences in reaching between healthy individuals. This novel quantitative assessment method may be used in conjunction with home-based gaming motion-capture technology for remote monitoring of motor deficits and inform the development of evidence-based robotic therapy interventions.
New and NoteworthyFunctional deficits seen in task performance have biomechanical underpinnings, seen only through the analysis of forces. Our study has shown that estimating muscle moments can quantify with high sensitivity post-stroke deficits in intersegmental coordination. An assessment developed based on this method could help quantify less observable deficits in mildly affected stroke patients. It may also bridge the gap between evidence from studies of constrained or robotically manipulated movements and research with functional and unconstrained movements. | neuroscience |
Influenza-specific effector memory B cells predict long-lived antibody responses to vaccination in humans Seasonal influenza vaccination elicits hemagglutinin (HA)-specific CD27+ memory B cells (Bmem) that differ in expression of T-bet, BACH2 and TCF7. T-bethiBACH2loTCF7lo Bmem are transcriptionally similar to effector-like memory cells while T-betloBACH2+TCF7+ Bmem exhibit stem-like central memory properties. T-bethi Bmem do not express plasma cell-specific transcription factors but do exhibit transcriptional, epigenetic, metabolic and functional changes that poise the cells for antibody production. Consistent with these changes, D7 HA+ T-bethi Bmem express intracellular immunoglobulin and T-bethi Bmem differentiate more rapidly into ASCs in vitro. The T-bethi Bmem response positively correlates with long-lived humoral immunity and clonotypes from T-bethi Bmem are represented in the early secondary ASC response to repeat vaccination, suggesting that this effector-like population can be used to predict vaccine durability and recall potential. | immunology |
Mutators drive evolution of multi-resistance to antibiotics Combination drug treatments are an approach used to counter the evolution of resistance-the guiding principle being that they can prevent multiple independent resistance mutations from arising sequentially in the same genome. Here, we show that bacterial populations with mutators, organisms defective in DNA repair, can evolve multi-resistance under conditions where purely wild-type populations cannot. We exposed experimental populations of Escherichia coli to rising concentrations of single-drug and combination antibiotic treatments. Introducing mutators at low-to-intermediate frequencies permitted the evolution of multi-resistance. Notably, the evolution of multi-resistance did not require direct selection for both resistance mutations, as the elevated mutation rates allowed it to evolve under single-drug and combination treatments alike. Using eco-evolutionary simulations, we show that hitch-hiking with single resistance mutations allowed the mutator allele to sweep to fixation. The resulting increase in mutation supply was the key to evolving multi-resistance sequentially. While simulations also demonstrated that multi-resistance can arise in large populations, the size required exceeded those typical of infection. Ultimately, our results suggest that the utility of combination therapy may be limited when mutators are present, and when achieving or maintaining therapeutic antibiotic concentrations is difficult. | evolutionary biology |
A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability In complex real-life motor skills such as unconstrained throwing, performance depends on how accurate is on average the outcome of noisy, high-dimensional, and redundant actions. What characteristics of the action distribution relate to performance and how different individuals select specific action distributions are key questions in motor control. Previous computational approaches have highlighted that variability along the directions of first order derivatives of the action-to-outcome mapping affects performance the most, that different mean actions may be associated to regions of the actions space with different sensitivity to noise, and that action covariation in addition to noise magnitude matters. However, a method to relate individual high-dimensional action distribution and performance is still missing. Here we introduce a de-composition of performance into a small set of indicators that compactly and directly characterize the key performance-related features of the distribution of high-dimensional redundant actions. Central to the method is the observation that, if performance is quantified as a mean score, the Hessian (second order derivatives) of the action-to-score function determines how the noise of the action distribution affects the average score. We can then approximate the mean score as the sum of the score of the mean action and a tolerance-variability index which depends on both Hessian and action covariance. Such index can be expressed as the product of three terms capturing noise magnitude, noise sensitivity, and alignment of the most variable and most noise sensitive directions. We apply this method to the analysis of unconstrained throwing actions by non-expert participants and show that, consistently across four different throwing targets, each participant shows a specific selection of mean action score and tolerance-variability index as well as specific selection of noise magnitude and alignment indicators. Thus, participants with different strategies may display the same performance because they can trade off suboptimal mean action for better tolerance-variability and higher action variability for better alignment with more tolerant directions in action space.
Author summaryWhy do people differ in their performance of complex motor skills? In many real-life motor tasks achieving a goal requires selecting an appropriate high-dimensional action out of infinitely many goal-equivalent actions. Because of sensorimotor noise, we are unable to execute the exact same movement twice and our performance depends on how accurate we are on average. Thus, to understand why people perform differently we need to characterize how their action distribution relates to their mean task score. While better performance is often associated to smaller variability around a more accurate mean action, performance also depends on the relationship between the directions of highest variability in action space and the directions in which action variability affects the most the outcome of the action. However, characterizing such geometric relationship when actions are high dimensional is challenging. In this work we introduce a method that allows to characterize the key performance-related features of the distribution of high-dimensional actions by a small set of indicators. We can then compare such indicators in different people performing a complex task (such as unconstrained throwing) and directly characterize the most skilled ones but also identify different strategies that distinguish people with similar performance. | neuroscience |
Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech population AO_SCPLOWBSTRACTC_SCPLOWSince several studies have been reporting an increase in the decline of forests, a major issue in ecology is to better understand and predict tree mortality. The interactions between the different factors and the physiological processes giving rise tree mortality, as well as the inter-individual variability in mortality risk, still need to be better assessed.
This study investigates mortality in a rear-edge population of European beech (Fagus sylvatica L.) using a combination of statistical and process-based modelling approaches. Based on a survey of 4323 adult beeches since 2002 within a natural reserve, we first used statistical models to quantify the effects of competition, tree growth, size, defoliation and fungi presence on mortality. Secondly, we used an ecophysiological process-based model (PBM) to separate out the different mechanisms giving rise to temporal and inter-individual variations in mortality by simulating depletion of carbon stocks, loss of hydraulic conductance and damage due to late frosts in response to climate.
The combination of all these simulated processes was associated with the temporal variations in the population mortality rate. The individual probability of mortality decreased with increasing mean growth, and increased with increasing crown defoliation, earliness of budburst, fungi presence and increasing competition, in the statistical model. Moreover, the interaction between tree size and defoliation was significant, indicating a stronger increase in mortality associated to defoliation in smaller than larger trees. Finally, the PBM predicted a higher conductance loss together with a higher level of carbon reserves for trees with earlier budburst, while the ability to defoliate the crown was found to limit the impact of hydraulic stress at the expense of the accumulation of carbon reserves.
We discuss the convergences and divergences obtained between statistical and process-based approaches and we highlight the importance of combining them to characterize the different processes underlying mortality, and the factors modulating individual vulnerability to mortality. | ecology |
Deconstructing taxa x taxa x environment interactions in the microbiota: A theoretical examination O_LIA major objective of microbial ecology is to identify how the composition of gut microbial taxa shapes host phenotypes. However, most studies focus solely on community-level patterns and pairwise interactions and ignore the potentially significant effects of higher-order interactions involving three or more component taxa.
C_LIO_LIStudies on higher-order interactions among microbial taxa are scarce for many reasons, including experimental intractability, daunting diversity and complexity of many microbial systems, and the potential confounding role of the environment. Moreover, we still lack the empirical and statistical tools to isolate and understand the role of higher-order interactions on the host.
C_LIO_LIHere, we apply a mathematical approach to quantifying the effects of higher-order interactions among taxa on host infection risk. To do so, we adapt the Hadamard-Walsh method recently used in evolutionary genetics to quantify the nonlinear effects of mutations on fitness. We apply our approach to an in silico dataset built to resemble a population of insect hosts with gut-associated microbial communities at risk of infection from an intestinal parasite. Critically, we examine these interactions across a breadth of environmental contexts, using nutrient content of the insect diet as a model for context.
C_LIO_LIWe find that the effect of higher-order interactions is considerable and can change appreciably across environmental contexts. Strikingly, the relative eminence of different orders (pairwise vs. third order, fourth order, and fifth order) changes as a function of environmental context. Furthermore, we show-in our theoretical microcosm-that higher-order interactions can stabilize community structure thereby reducing host susceptibility to parasite invasion.
C_LIO_LIOur approach illustrates how incorporating the effects of higher-order interactions among gut microbiota across environments can be essential for understanding their effects on host phenotypes. We conclude that higher-order interactions among taxa can profoundly shape important organismal phenotypes, and they deserve greater attention in host-associated microbiome studies.
C_LI | ecology |
Damped oscillations of the probability of random events followed by absolute refractory period: exact analytical results There are numerous examples of natural and artificial processes that represent stochastic sequences of events followed by an absolute refractory period during which the occurrence of a subsequent event is impossible. In the simplest case of a generalized Bernoulli scheme for uniform random events followed by the absolute refractory period, the event probability as a function of time can exhibit damped transient oscillations. Using stochastically-spiking point neuron as a model example, we present an exact and compact analytical description for the oscillations without invoking the standard renewal theory. The resulting formulas stand out for their relative simplicity, allowing one to analytically obtain the amplitude damping of the 2nd and 3rd peaks of the event probability. | neuroscience |
Estimations of the weather effects on brain functions using functional MRI: a cautionary note The influences of environmental factors such as weather on the human brain are still largely unknown. A few neuroimaging studies have demonstrated seasonal effects, but were limited by their cross-sectional design or sample sizes. Most importantly, the stability of the MRI scanner hasnt been taken into account, which may also be affected by environments. In the current study, we analyzed longitudinal resting-state functional MRI (fMRI) data from eight individuals, where the participants were scanned over months to years. We applied machine learning regression to use different resting-state parameters, including the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity matrix, to predict different weather and environmental parameters. For careful control, the raw EPI and the anatomical images were also used for predictions. We first found that daylight length and air temperatures could be reliably predicted with cross-validation using the resting-state parameters. However, similar prediction accuracies could also be achieved by using one frame of EPI image, and even higher accuracies could be achieved by using segmented or raw anatomical images. Finally, the signals outside of the brain in the anatomical images and signals in phantom scans could also achieve higher prediction accuracies, suggesting that the predictability may be due to the baseline signals of the MRI scanner. After all, we did not identify detectable influences of weather on brain functions other than the influences on the baseline signals of MRI scanners. The results highlight the difficulty of studying long-term effects using MRI. | neuroscience |
Secondary Structure Motifs Made Searchable to Facilitate the Functional Peptide Design To ensure a physicochemically desired sequence motif to adapt a specific type of secondary structures, we compile an -helix database allowing complicate search patterns to facilitate a data-driven design of therapeutic peptides. Nearly 1.7 million helical peptides in >130 thousand proteins are extracted along with their interacting partners from the protein data bank (PDB). The sequences of the peptides are indexed with patterns and gaps and deposited in our Therapeutic Peptide Design dataBase (TP-DB). We here demonstrate its utility in three medicinal design cases. By our pattern-based search engine but not PHI-BLAST, we can identify a pathogenic protein, Helicobacter pylori neutrophil-activating protein (HP-NAP), a virulence factor of H. pylori, which contains a motif DYKYLE that belongs to the affinity determinant motif DYKXX[DE] of the FLAG-tag and can be recognized by the anti-FLAG M2 antibody. By doing so, the known purification-tag-specific antibody is repurposed into a diagnostic kit for H. pylori. Also by leveraging TP-DB, we discovered a stretch of helical peptide matching the potent membrane-insertion pattern WXXWXXW, elucidated by MD simulations. The newly synthesized peptide has a better minimal inhibitory concentration (MIC) and much lower cytotoxicity against Candida albicans (fungus) than that of previously characterized homologous antimicrobial peptides. In a similar vein, taking the discontinued anchoring residues in the helix-helix interaction interface as the search pattern, TP-DB returns several helical peptides as potential tumor suppressors of hepatocellular carcinoma (HCC) whose helicity and binding affinity were examined by MD simulations. Taken together, we believe that TP-DB and its pattern-based search engine provide a new opportunity for a (secondary-)structure-based design of peptide drugs and diagnostic kits for pathogens without inferring evolutionary homology between sequences sharing the same pattern. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/. | bioinformatics |
Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations The biomass equation is a critical component in genome-scale metabolic models (GEMs): it is used as the de facto objective function in flux balance analysis (FBA). This equation accounts for the quantities of all known biomass precursors that are required for cell growth based on the macromolecular and monomer compositions measured at certain conditions. However, it is often reported that the macromolecular composition of cells could change across different environmental conditions; the use of the same single biomass equation in FBA, under multiple conditions, is questionable. Thus, we first investigated the qualitative and quantitative variations of macromolecular compositions of three representative host organisms, Escherichia coli, Saccharomyces cerevisiae and Cricetulus griseus, across different environmental/genetic variations. While macromolecular building blocks such as DNA, RNA, protein, and lipid composition vary notably, variations in fundamental biomass monomer units such as nucleotides and amino acids are not appreciable. We further observed that while macromolecular compositions are similar across taxonomically closer species, certain monomers, especially fatty acids, vary substantially. Based on the analysis results, we subsequently propose a new extension to FBA, named "Flux Balance Analysis with Ensemble Biomass (FBAwEB)", to embrace the natural variation in selected components of the biomass equation. The current study clearly highlights that certain components of the biomass equation are very sensitive to different conditions, and the ensemble representation of biomass equation in the FBA framework enables us to account for such natural variations accurately during GEM-guided in silico simulations. | systems biology |
Molecular Determinants of μ-Conotoxin KIIIA interaction with the Voltage-Gated Sodium Channel Nav1.7 The voltage-gated sodium (Nav) channel subtype Nav1.7 plays a critical role in pain signaling, making it an important drug target. Here we studied the molecular interactions between -conotoxin KIIIA (KIIIA) and the human Nav1.7 channel (hNav1.7). We developed a structural model of hNav1.7 using Rosetta computational modeling and performed in silico docking of KIIIA using RosettaDock to predict residues forming specific pairwise contacts between KIIIA and hNav1.7. We experimentally validated these contacts using mutant cycle analysis. Comparison between our KIIIA-hNav1.7 model and the cryo-EM structure of KIIIA-hNav1.2 revealed key similarities and differences between Nav channel subtypes with potential implications for the molecular mechanism of toxin block. The accuracy of our integrative approach, combining structural data with computational modeling, experimental validation, and molecular dynamics simulations, suggests that Rosetta structural predictions will be useful for rational design of novel biologics targeting specific Nav channels. | biophysics |
Deep learning does not outperform classical machine learning for cell-type annotation Deep learning has revolutionized image analysis and natural language processing with remarkable accuracies in prediction tasks, such as image labeling and semantic segmentation or named-entity recognition and semantic role labeling. Specifically, the combination of algorithmic and hardware advances with the appearance of large and well-labeled datasets has led up to seminal contributions in these fields.
The emergence of large amounts of data from single-cell RNA-seq and the recent global effort to chart all cell types in the Human Cell Atlas has attracted an interest in deep-learning applications. However, all current approaches are unsupervised, i.e., learning of latent spaces without using any cell labels, even though supervised learning approaches are often more powerful in feature learning and the most popular approach in the current AI revolution by far. Here, we ask why this is the case. In particular we ask whether supervised deep learning can be used for cell annotation, i.e. to predict cell-type labels from single-cell gene expression profiles. After evaluating 10 classification methods across 14 datasets, we notably find that deep learning does not outperform classical machine-learning methods in the task. Thus, cell-type prediction based on gene-signature derived cell-type labels is potentially too simplistic a task for complex non-linear methods, which demands better labels of functional single-cell readouts. | bioinformatics |
Regulatory regions in natural transposable element insertions drive interindividual differences in response to immune challenges in Drosophila BackgroundVariation in gene expression underlies interindividual variability in relevant traits including immune response. However, the genetic variation responsible for these gene expression changes remain largely unknown. Among the non-coding variants that could be relevant, transposable element insertions are promising candidates as they have been shown to be a rich and diverse source of cis-regulatory elements.
ResultsIn this work, we used a population genetics approach to identify transposable element insertions likely to increase the tolerance of Drosophila melanogaster to bacterial infection by affecting the expression of immune-related genes. We identified 12 insertions associated with allele-specific expression changes in immune-related genes. We experimentally validated three of these insertions including one likely to be acting as a silencer, one as an enhancer, and one with a dual role as enhancer and promoter. The direction in the change of gene expression associated with the presence of several of these insertions was consistent with an increased survival to infection. Indeed, for one of the insertions, we showed that this is the case by analyzing both natural populations and CRISPR/Cas9 mutants in which the insertion was deleted from its native genomic context.
ConclusionsWe showed that transposable elements contribute to gene expression variation in response to infection in D. melanogaster and that this variation is likely to affect their survival capacity. Because the role of transposable elements as regulatory elements is not restricted to Drosophila, TEs are likely to play a role in immune response in other organisms as well. | evolutionary biology |
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