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Genetic Association Study of Childhood Aggression across raters, instruments and age Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data - i.e. within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE=0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg =0.46 between self- and teacher-assessment to rg =0.81 between mother- and teacher-assessment. We obtained moderate to strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg| : 0.19 - 1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =~ -0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46 - 0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.
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genomics
|
Constitutively enhanced genome integrity maintenance and direct stress mitigation characterize transcriptome of extreme stress-adapted Arabidopsis halleri Heavy metal-rich toxic soils and ordinary soils are both natural habitats of Arabidopsis halleri. The molecular divergence underlying survival in sharply contrasting environments is unknown. Here we comparatively address metal physiology and transcriptomes of A. halleri originating from the most highly heavy metal-contaminated soil in Europe, Ponte Nossa (Noss/IT), and from non-metalliferous (NM) soil. Noss exhibits enhanced hypertolerance and attenuated accumulation of cadmium (Cd), and transcriptomic Cd responsiveness is decreased, compared to plants of NM soil origin. Among the condition-independent transcriptome characteristics of Noss, the most highly overrepresented functional class of "meiotic cell cycle" comprises 21 transcripts with elevated abundance in vegetative tissues, in particular Argonaute 9 (AGO9) and the synaptonemal complex transverse filament protein-encoding ZYP1a/b. Increased AGO9 transcript levels in Noss are accompanied by decreased long terminal repeat retrotransposon expression, and are shared by plants from milder metalliferous sites in Poland and Germany. Expression of Iron-regulated Transporter (IRT1) is very low and of Heavy Metal ATPase 2 (HMA2) strongly elevated in Noss, which can account for its specific Cd handling. In plants adapted to the most extreme abiotic stress, broadly enhanced functions comprise genes with likely roles in somatic genome integrity maintenance, accompanied by few alterations in stress-specific functional networks.
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plant biology
|
BitEpi: A Fast and Accurate Exhaustive Higher-Order Epistasis Search MotivationComplex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved.
ResultsIn this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.e. Single Nucleotide Variant or SNV for short). BitEpi introduces a novel bitwise algorithm that is 2.1 and 56 times faster for 3-SNV and 4-SNV search, than established software. The novel entropy statistic used in BitEpi is 44% more accurate to identify interactive SNVs, incorporating a p-value-based significance testing. We demonstrate BitEpi on real world data of 4,900 samples and 87,000 SNPs. We also present EpiExplorer to visualize the potentially large number of individual and interacting SNVs in an interactive Cytoscape graph. EpiExplorer uses various visual elements to facilitate the discovery of true biological events in a complex polygenic environment.
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bioinformatics
|
A cross-nearest neighbor/Monte Carlo algorithm for single molecule localization microscopy defines interactions between p53, Mdm2, and MEG3 The functions of long noncoding (lnc)RNAs such as MEG3 are defined by their interactions with other RNAs and proteins. These interactions, in turn, are shaped by their subcellular localization and temporal context. Therefore, it is important to be able to analyze the relationships of lncRNAs while preserving cellular architecture. The ability of MEG3 to suppress cell proliferation led to its recognition as a tumor suppressor. MEG3 has been proposed to activate p53 by disrupting the interaction of p53 with Mdm2. To test this mechanism in the native cellular context, we employed two-color direct stochastic optical reconstruction microscopy (dSTORM), a single-molecule localization microscopy (SMLM) technique to detect and quantify the localizations of p53, Mdm2, and MEG3 in U2OS cells. We developed a new cross-nearest neighbor/Monte Carlo algorithm to quantify the association of these molecules. Proof of concept for our method was obtained by examining the association between FKBP1A and mTOR, MEG3 and p53, and Mdm2 and p53. In contrast to previous models, our data support a model in which MEG3 modulates p53 independently of the interaction with Mdm2.
|
cell biology
|
Astral microtubule crosslinking by Feo safeguards uniform nuclear distribution in the Drosophila syncytium The early insect embryo develops as a multinucleated cell distributing the genome uniformly to the cell cortex. Mechanistic insight for nuclear positioning beyond cytoskeletal requirements is missing. Contemporary hypotheses propose actomyosin driven cytoplasmic movement transporting nuclei, or repulsion of neighbor nuclei driven by microtubule motors. Here, we show that microtubule crosslinking by Feo and Klp3A is essential for nuclear distribution and internuclear distance maintenance in Drosophila. Germline knockdown causes irregular, less dense nuclear delivery to the cell cortex and smaller distribution in ex vivo embryo explants. A minimal internuclear distance is maintained in explants from control embryos but not from Feo inhibited embryos, following micromanipulation assisted repositioning. A dimerization deficient Feo abolishes nuclear separation in embryo explants while the full-length protein rescues the genetic knockdown. We conclude that Feo and Klp3A crosslinking of antiparallel microtubule overlap generates a length-regulated mechanical link between neighboring microtubule asters. Enabled by a novel experimental approach, our study illuminates an essential process of embryonic multicellularity.
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cell biology
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Advancing motion denoising of multiband resting state functional connectivity fMRI data Simultaneous multi-slice (multiband) accelerated functional magnetic resonance imaging (fMRI) provides dramatically improved temporal and spatial resolution for resting-state functional connectivity (RSFC) studies of the human brain in health and disease. However, multiband acceleration also poses unique challenges for denoising of subject motion induced data artifacts, the presence of which is a major confound in RSFC research that substantively diminishes reliability and reproducibility. We comprehensively evaluated existing and novel approaches to volume censoring-based motion denoising in the Human Connectome Project (HCP) dataset. We show that assumptions underlying common metrics for evaluating motion denoising pipelines, especially those based on quality control-functional connectivity (QC-FC) correlations and differences between high- and low-motion participants, are problematic, and appear to be inappropriate in their current widespread use as indicators of comparative pipeline performance and as targets for investigators to use when tuning pipelines for their own datasets. We further develop two new quantitative metrics that are instead agnostic to QC-FC correlations and other measures that rely upon the null assumption that no true relationships exist between trait measures of subject motion and functional connectivity, and demonstrate their use as benchmarks for comparing volume censoring methods. Finally, we develop and validate quantitative methods for determining dataset-specific optimal volume censoring parameters prior to the final analysis of a dataset, and provide straightforward recommendations and code for all investigators to apply this optimized approach to their own RSFC datasets.
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neuroscience
|
17q21.31 sub-haplotypes underlying H1-associated risk for Parkinsons disease are associated with LRRC37A/2 expression in astrocytes Parkinsons disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. To better understand the genetic contribution of this region to PD, we fine-mapped the 17q21.31 locus in order to identify novel mechanisms conferring risk for the disease. We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble -synuclein, and co-localized with Lewy bodies in PD brain tissue. These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with -synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.
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neuroscience
|
Accurate modeling of replication rates in genome-wide association studies by accounting for winner's curse and study-specific heterogeneity Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex human traits, but only a fraction of variants identified in discovery studies achieve significance in replication studies. Replication in GWAS has been well-studied in the context of Winners Curse, which is the inflation of effect size estimates for significant variants due to statistical chance. However, Winners Curse is often not sufficient to explain lack of replication. Another reason why studies fail to replicate is that there are fundamental differences between the discovery and replication studies. A confounding factor can create the appearance of a significant finding while actually being an artifact that will not replicate in future studies. We propose a statistical framework that utilizes GWAS and replication studies to jointly model Winners Curse and study-specific heterogeneity due to confounding factors. We apply this framework to 100 GWAS from the Human GWAS Catalog and observe that there is a large range in the level of estimated confounding. We demonstrate how this framework can be used to distinguish when studies fail to replicate due to statistical noise and when they fail due to confounding.
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bioinformatics
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Comparative population genetic structure of two ixodid tick species (Ixodes ovatus and Haemaphysalis flava) in Niigata Prefecture, Japan Ixodid tick species such as Ixodes ovatus and Haemaphysalis flava are essential vectors of tick-borne diseases in Japan. In this study, we investigated the population genetic structures and gene flow of I. ovatus and H. flava as affected by the tick host mobility. We hypothesized that I. ovatus and H. flava may have differences in their genetic structure due to the low mobility of small rodent hosts of I. ovatus at the immature stage in contrast to the mediated dispersal of avian hosts for immature H. flava. We collected 307 adult I. ovatus and 220 adult H. flava from 29 and 17 locations across Niigata Prefecture, Japan. We investigated the genetic structure at two mitochondrial loci (cox1, 16S rRNA gene). For I. ovatus, pairwise FST and analysis of molecular variance (AMOVA) analyses of cox1 sequences indicated significant genetic variation among populations. Both cox1 and 16S rRNA markers showed non-significant genetic variation among locations for H. flava. The Bayesian tree and haplotype network of cox1 marker for I. ovatus samples in Niigata Prefecture found 3 genetic groups wherein most haplotypes in group 2 were distributed in low altitudinal areas. When we added cox1 sequences of I. ovatus from China to the phylogenetic analysis, three genetic groups (China 1, China 2, and Niigata and Hokkaido, Japan) were formed in the tree suggesting the potential for cryptic species in the genetic group in Japan. Our results support our hypothesis and suggest that the host preference of ticks at the immature stage may influence the genetic structure and gene flow of the ticks. This information is vital in understanding the tick-host interactions in the field to better understand the tick-borne disease transmission and in designing an effective tick control program.
|
genetics
|
The CDK8 inhibitor DCA promotes a tolerogenic chemical immunophenotype in CD4+ T cells via a novel CDK8-GATA3-FOXP3 pathway Immune health requires innate and adaptive immune cells to engage precisely balanced pro- and anti-inflammatory forces. We employ the concept of chemical immunophenotypes to classify small molecules functionally or mechanistically according to their patterns of effects on primary innate and adaptive immune cells. The high-specificity, low-toxicity cyclin dependent kinase 8 (CDK8) inhibitor DCA exerts a distinct tolerogenic profile in both innate and adaptive immune cells. DCA promotes Treg and Th2 differentiation, while inhibiting Th1 and Th17 differentiation, in both murine and human cells. This unique chemical immunophenotype led to mechanistic studies showing that DCA promotes Treg differentiation in part by regulating a previously undescribed CDK8-GATA3-FOXP3 pathway that regulates early pathways of Foxp3 expression. These results highlight previously unappreciated links between Treg and Th2 differentiation and extend our understanding of the transcription factors that regulate Treg differentiation and their temporal sequencing. These findings have significant implications for future mechanistic and translational studies of CDK8 and CDK8 inhibitors.
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immunology
|
Neural Fragility as an EEG Marker of the Seizure Onset Zone Over 15 million epilepsy patients worldwide do not respond to drugs. Successful surgical treatment requires complete removal, or disconnection of the seizure onset zone (SOZ), brain region(s) where seizures originate. Unfortunately, surgical success rates vary between 30%-70% because no clinically validated biological marker of the SOZ exists. We develop and retrospectively validate a new EEG marker - neural fragility - in a retrospective analysis of 91 patients by using neural fragility of the annotated SOZ as a metric to predict surgical outcomes. Fragility predicts 43/47 surgical failures with an overall prediction accuracy of 76%, compared to the accuracy of clinicians being 48% (successful outcomes). In failed outcomes, we identify fragile regions that were untreated. When compared to 20 EEG features proposed as SOZ markers, fragility outperformed in predictive power and interpretability suggesting neural fragility as an EEG biomarker of the SOZ.
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neuroscience
|
Corollary Discharge Promotes a Sustained Motor State in a Neural Circuit for Navigation Animals exhibit behavioral and neural responses that persist on longer time scales than transient or fluctuating stimulus inputs. Here, we report that C. elegans uses feedback from the motor circuit to a sensory processing interneuron to sustain its motor state during thermotactic navigation. By imaging circuit activity in behaving animals, we show that a principal postsynaptic partner of the AFD thermosensory neuron, the AIY interneuron, encodes both temperature and motor state information. By optogenetic and genetic manipulation of this circuit, we demonstrate that the motor state representation in AIY is a corollary discharge signal. RIM, an interneuron that is connected with premotor interneurons, is required for this corollary discharge. Ablation of RIM eliminates the motor representation in AIY, allows thermosensory representations to reach downstream premotor interneurons, and reduces the animals ability to sustain forward movements during thermotaxis. We propose that feedback from the motor circuit to the sensory processing circuit underlies a positive feedback mechanism to generate persistent neural activity and sustained behavioral patterns in a sensorimotor transformation.
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neuroscience
|
Decay and damage of therapeutic phage OMKO1 by environmental stressors Antibiotic resistant bacterial pathogens are increasingly prevalent, driving the need for alternative approaches to chemical antibiotics when treating infections. One such approach is bacteriophage therapy: the use of bacteria-specific viruses that lyse (kill) their host cells. Just as the effect of environmental conditions (e.g. elevated temperature) on antibiotic efficacy is well-studied, the effect of environmental stressors on the potency of phage therapy candidates demands examination. Therapeutic phage OMKO1 infects and kills the opportunistic human pathogen Pseudomonas aeruginosa. Here, we used phage OMKO1 as a model to test how different environments affect the decay rate of a therapeutic virus, and whether exposure to an environmental stressor can damage surviving viral particles. We assessed the effects of elevated temperatures, saline concentrations, and urea concentrations. We observed that OMKO1 particles were highly tolerant to different saline concentrations, but decayed more rapidly at elevated temperatures and under high concentrations of urea. Additionally, we found that exposure to elevated temperature reduced the ability of surviving phage particles to suppress the growth of P. aeruginosa, suggesting a temperature-induced damage. Our findings demonstrate that OMKO1 is highly tolerant to a range of conditions that could be experienced inside and outside the human body, while also showing the need for careful characterization of therapeutic phages to ensure that environmental exposure does not compromise their expected potency, dosing, and pharmacokinetics.
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microbiology
|
Spike-timing-dependent plasticity rewards synchrony rather than causality Spike-timing-dependent plasticity (STDP) is a candidate mechanism for information storage in the brain, but the whole-cell recordings required for the experimental induction of STDP are typically limited to one hour. This mismatch of time scales is a long-standing weakness in synaptic theories of memory. Here we use spectrally separated optogenetic stimulation to fire precisely timed action potentials (spikes) in CA3 and CA1 pyramidal cells. Twenty minutes after optogenetic induction of STDP (oSTDP), we observed timing-dependent depression (tLTD) and timing-dependent potentiation (tLTP), depending on the sequence of spiking. As oSTDP does not require electrodes, we could also assess the strength of these paired connections three days later. At this late time point, late tLTP was observed for both causal (CA3 before CA1) and anti-causal (CA1 before CA3) timing, but not for asynchronous activity patterns ({Delta}t = 50 ms). Blocking activity after induction of oSTDP prevented stable potentiation. Our results confirm that neurons wire together if they fire together, but suggest that synaptic depression after anti-causal activation (tLTD) is a transient phenomenon.
HighlightsO_LIOptogenetic induction of spike-timing-dependent plasticity at Schaffer collateral synapses
C_LIO_LICausal pairing induces potentiation whereas anti-causal pairing induces depression during patch-clamp recordings.
C_LIO_LIThree days after optogenetic induction, the consequence of STDP is potentiation (tLTP) irrespective of spiking order.
C_LIO_LILate tLTP requires ongoing activity in the days following oSTDP.
C_LI
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/863365v4_ufig1.gif" ALT="Figure 1">
View larger version (19K):
[email protected]@16566f8org.highwire.dtl.DTLVardef@4b4a73org.highwire.dtl.DTLVardef@104fc97_HPS_FORMAT_FIGEXP M_FIG C_FIG
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neuroscience
|
Discoidin domain receptor 2 drives melanoma drug resistance through AXL-dependent phenotype switching Anti-BRAF plus anti-MEK are used as first-line treatment of patients with metastatic melanomas harboring BRAF V600E mutation. The main issue with targeted therapy is acquired cellular resistance. In 70% of acquired resistance, melanoma cells switch their phenotype and become more aggressive and invasive. The molecular signature of this phenotype is MITF low, AXL high associated with actin cytoskeleton reorganization. After this switch, resistant cells present an anarchic cell proliferation due to MAP kinase pathway hyper-activation. We demonstrate that resistant cell lines presenting phenotype switching overexpress DDR1 and DDR2. We show that DDR2 inhibition induces a decrease in AXL and reduces actin stress fiber formation. Once this phenotype switching is acquired, we report that both DDRs promotes tumor cell proliferation, but only DDR2 can over-activate the MAP kinase pathway in resistant invasive cells in vitro and in vivo. Therefore, DDRs inhibition could be a promising strategy for countering this resistance mechanism.
SignificanceOur results show that DDR2 is a relevant target in melanoma resistance. DDR2 is required at the beginning of resistance for melanoma cell phenotype switching to occur. After phenotype switching, DDRs promote tumor cell proliferation of resistant invasive melanoma cells, but only DDR2 is able to over-activate the MAP kinase pathway. We put forward dasatinib (a DDR inhibitor) as a potential second-line treatment after targeted dual therapy for resistant patients overexpressing DDRs.
|
cancer biology
|
Chromatin-accessibility estimation of single-cell ATAC data with scOpen A major drawback of single cell ATAC (scATAC) is its sparsity, i.e. open chromatin regions with no reads due to loss of DNA material during the scATAC-seq protocol. We propose scOpen, a computational method for imputing and quantifying the open chromatin status of regulatory regions from sparse scATAC-seq experiments. We show that scOpen improves crucial down-stream analysis steps of scATAC-seq data as clustering, visualisation, cis-regulatory DNA interactions and delineation of regulatory features. We demonstrate the power of scOpen to dissect regulatory changes in the development of fibrosis in the kidney. This identified a novel role of Runx1 and target genes by promoting fibroblast to myofibroblast differentiation driving kidney fibrosis.
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bioinformatics
|
Base-pair resolution analysis of the effect of supercoiling on DNA flexibility and major groove recognition by triplex-forming oligonucleotides In the cell, DNA is arranged into highly-organised and topologically-constrained (supercoiled) structures. It remains unclear how this supercoiling affects the detailed double-helical structure of DNA, largely because of limitations in spatial resolution of the available biophysical tools. Here, we overcome these limitations, by a combination of atomic force microscopy (AFM) and atomistic molecular dynamics (MD) simulations, to resolve structures of negatively-supercoiled DNA minicircles at base-pair resolution. We observe that negative superhelical stress induces local variation in the canonical B-form DNA structure by introducing kinks and defects that affect global minicircle structure and flexibility. We probe how these local and global conformational changes affect DNA interactions through the binding of triplex-forming oligonucleotides to DNA minicircles. We show that the energetics of triplex formation is governed by a delicate balance between electrostatics and bonding interactions. Our results provide mechanistic insight into how DNA supercoiling can affect molecular recognition, that may have broader implications for DNA interactions with other molecular species.
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biophysics
|
Grapevine rootstocks affect growth-related scion phenotypes Grape growers use rootstocks to provide protection against pests and pathogens and to modulate viticulture performance such as shoot growth. Our study examined two grapevine scion varieties ( Chardonnay and Cabernet Sauvignon) grafted to 15 different rootstocks and determined the effect of rootstocks on eight traits important to viticulture. We assessed the vines across five years and identified both year and variety as contributing strongly to trait variation. The effect of rootstock was relatively consistent across years and varieties, explaining between 8.99% and 9.78% of the variation in growth-related traits including yield, pruning weight, berry weight, and Ravaz index (yield to pruning weight ratio). Increases in yield due to rootstock were generally the result of increases in berry weight, likely due to increased water uptake by vines grafted to a particular rootstock. We demonstrated a greater than 50% increase in yield, pruning weight, or Ravaz index by choosing the optimal rootstock, indicating that rootstock choice is crucial for grape growers looking to improve vine performance.
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plant biology
|
Dopamine differentially modulates the size of projection neuron ensembles in the intact and dopamine-depleted striatum Dopamine (DA) is a critical modulator of brain circuits that control voluntary movements, but our understanding of its influence on the activity of target neurons in vivo remains limited. Here, we use two-photon Ca2+ imaging to monitor the activity of direct and indirect-pathway spiny projection neurons (SPNs) simultaneously in the striatum of behaving mice during acute and prolonged manipulations of DA signaling. We find that increasing and decreasing DA biases striatal activity towards the direct and indirect pathways, respectively, by changing the overall number of SPNs recruited during behavior in a manner not predicted by existing models of DA function. This modulation is drastically altered in a model of Parkinsons disease. Our results reveal a previously unappreciated population-level influence of DA on striatal output and provide novel insights into the pathophysiology of Parkinsons disease.
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neuroscience
|
Plant size, leaf economics, and their diversity are strong controls of tundra carbon cycling O_LIThe functional composition and diversity of plant communities are globally applicable predictors of ecosystem functioning. Yet, it is unclear how traits influence carbon cycling. This is an important question in the tundra where vegetation shifts are occurring across the entire biome, and where soil organic carbon stocks are large and vulnerable to environmental change.
C_LIO_LITo study how traits affect carbon cycling in the tundra, we built a model that explained carbon cycling (above-ground and soil organic carbon stocks, and photosynthetic and respiratory fluxes) with abiotic conditions (air temperature and soil moisture), plant community functional composition (average plant height, leaf dry matter content (LDMC) and specific leaf area (SLA)), and functional diversity (weighted standard deviations of the traits). Data was collected from an observational study setting from northern Finland.
C_LIO_LIThe explanatory power of the models was relatively high, but a large part of variation in soil organic carbon stocks remained unexplained. Plant height was the strongest predictor of all carbon cycling variables except soil carbon stocks. Communities of larger plants were associated with larger CO2 fluxes and above-ground carbon stocks. Communities with fast leaf economics (i.e. high SLA and low LDMC) had higher photosynthesis, ecosystem respiration, and soil organic carbon stocks.
C_LIO_LIWithin-community variability in plant height, SLA, and LDMC affected ecosystem functions differently. SLA and LDMC diversity increased CO2 fluxes and soil organic carbon stocks, while height diversity increased the above-ground carbon stock. The contributions of functional diversity metrics to ecosystem functioning were about as important as those of average SLA and LDMC traits.
C_LIO_LISynthesis: Plant height, SLA, and LDMC have clear effects on tundra carbon cycling. The importance of functional diversity highlights a potentially important mechanism controlling the vast tundra carbon pools that should be better recognized. More research on root traits and decomposer communities is needed to understand the below-ground mechanisms regulating carbon cycling in the tundra.
C_LI
|
ecology
|
Antagonistic plants preferentially target arbuscular mycorrhizal fungi that are highly connected to mutualistic plants O_LIHow antagonists - mycoheterotrophic plants that obtain carbon and soil nutrients from fungi - are integrated in the usually mutualistic arbuscular mycorrhizal networks is unknown. Here, we compare mutualistic and antagonistic plant associations with arbuscular mycorrhizal fungi and use network analysis to investigate fungal association preferences in the tripartite network.
C_LIO_LIWe sequenced root tips from mutualistic and antagonistic plants in a tropical forest to assemble the combined tripartite network between mutualistic plants, mycorrhizal fungi, and antagonistic plants. We compared the fungal ecological similarity between mutualistic and antagonist networks, and searched for modules (an antagonistic and a mutualistic plant interacting with the same pair of fungi) to investigate whether pairs of fungi simultaneously linked to plant species from each interaction type were overrepresented throughout the network.
C_LIO_LIAntagonistic plants interacted with approximately half the fungi detected in mutualistic plants. Antagonists were indirectly linked to any of the detected mutualistic plants, and fungal pairwise ecological distances were correlated in both network types. Moreover, pairs of fungi sharing the same antagonistic and mutualistic plant species occurred more often than expected by chance.
C_LIO_LIWe hypothesize that the maintenance of antagonistic interactions is maximized by targeting well-linked mutualistic fungi, thereby minimizing the risk of carbon supply shortages.
C_LI
|
ecology
|
Differential tolerance of Zymoseptoria tritici to altered optimal moisture conditions during the early stages of wheat infection Foliar plant pathogens require liquid or vapour water for at least part of their development, but their response and their adaptive tolerance to moisture conditions have been much less studied than other meteorological factors to date. We examined the impact on the wheat-Zymoseptoria tritici interaction of altering optimal moisture conditions conducive to infection. We assessed the responses in planta of 48 Z. tritici strains collected in two climatologically distinct locations (Ireland and Israel) to four high moisture regimes differing in the timing and the duration of uninterrupted exposure to saturated relative humidity (100% RH) during the first three days of infection. Individual- and population-level moisture reaction norms expressing how the sporulating area of a lesion change with the RH conditions were established based on visual assessments of lesion development at 14, 17 and 20 days post-inoculation (dpi). Our findings highlighted: (i) a critical time-dependent effect on lesion development of uninterrupted periods of exposure to 100% RH during these earliest infection stages; (ii) a marked interindividual variation in the sensitivity to RH conditions both in terms of strain average moisture response and plasticity; (iii) a higher tolerance - expressed at 14 dpi, not later - of the Israeli population to early interruption of optimal moisture conditions. By indicating that sensitivity to sub-optimal moisture conditions may vary greatly between Z. tritici individuals and populations, this study highlights the evidence of moisture adaptation signature in a plant pathogen. This suggests that understanding such variation will be critical to predict their response to changing climatic conditions.
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microbiology
|
Characterization and rescue by oxytocin of an atypical thermo-sensory reactivity in neonatal mice lacking the autism-associated gene Magel2. Atypical responses to sensory stimuli are considered as a core aspect and early life marker of autism spectrum disorders (ASD). Although recent findings performed in mouse ASD genetic models report sensory deficits, these were explored exclusively during juvenile or adult period. Whether sensory dysfunctions might be present at the early life stage and rescued by therapeutic strategy are fairly uninvestigated. Here we identified that neonatal mice lacking the autism-associated gene Magel2 fail to react to cool sensory stimuli, while autonomic thermoregulatory function is active. This neonatal deficit was mimicked in control neonates by chemogenetic inactivation of oxytocin neurons. Importantly, intranasal administration of oxytocin was able to rescue the phenotype and brain Erk signaling impairment in mutants. This preclinical study establishes for the first-time early life impairments in thermosensory integration and shows the therapeutic potential benefits of intranasal oxytocin treatment on neonatal atypical sensory reactivity.
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neuroscience
|
A novel cis regulatory element regulates human XIST in CTCF-dependent manner The long non-coding RNA XIST is the master regulator for the process of X chromosome inactivation (XCI) in mammalian females. Here we report the existence of a hitherto uncharacterized cis regulatory element (cRE) within the first exon of human XIST, which determines the transcriptional status of XIST during the initiation and maintenance phases of XCI. In the initiation phase, pluripotency factors bind to this cRE and keep XIST repressed. In the maintenance phase of XCI, the cRE is enriched for CTCF which activates XIST transcription. By employing a CRISPR-dCas9-KRAB based interference strategy, we demonstrate that binding of CTCF to the newly identified cRE is critical for regulating XIST in a YY1-dependent manner. Collectively, our study uncovers the combinatorial effect of multiple transcriptional regulators influencing XIST expression during the initiation and maintenance phases of XCI.
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genomics
|
Analytical solution of linearized equations of the Morris-Lecar neuron model at large constant stimulation The classical biophysical Morris-Lecar model of neuronal excitability predicts that upon stimulation of the neuron with a sufficiently large constant depolarizing current there exists a finite interval of the current values where periodic spike generation occurs. Above the upper boundary of this interval, there is four-stage damping of the spike amplitude: 1) minor primary damping, which reflects a typical transient to stationary dynamic state, 2) plateau of nearly undamped periodic oscillations, 3) strong damping, and 4) reaching a constant asymptotic value of the neuron potential. We have shown that in the vicinity of the asymptote the Morris-Lecar equations can be reduced to the standard equation for exponentially damped harmonic oscillations. Importantly, all coefficients of this equation can be explicitly expressed through parameters of the original Morris-Lecar model, enabling direct comparison of the numerical and analytical solutions for the neuron potential dynamics at later stages of the spike amplitude damping.
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neuroscience
|
Clumpy coexistence in phytoplankton: The role of functional similarity in community assembly AO_SCPLOWBSTRACTC_SCPLOWEmergent neutrality (EN) suggests that species must be sufficiently similar or sufficiently different in their niches to avoid interspecific competition. Such a scenario results in a transient pattern with clumps and gaps of species abundance along the niche axis (e.g., represented by body size). From this perspective, clumps are groups of coexisting species with negligible fitness differences and stochastic abundance fluctuations. Plankton is an excellent model system for developing and testing ecological theories, especially those related to size structure and species coexistence. We tested EN predictions using the phytoplankton community along the course of a tropical river considering (i) body size structure, (ii) functional clustering of species in terms of morphology-based functional groups (MBFG), and (iii) the functional similarity among species concerning their functional traits. Two main clumps in the body size axis (clump I and II) were conspicuous through time and were detected in different stretches of the river. Clump I comprised medium-sized species from the MBFGs IV, V, and VI while clump II included large-bodied species from the MBFGs V and VI. Pairwise differences in species biovolume correlated with species functional similarity when the whole species pool was considered, but not among species within the same clump. Although clumps comprised multiple MBFGs, the dominant species within the clump belonged always to the same MBFG. Also, within-clump species biovolume increased with functional distinctiveness considering both seasons and stretches, except the lower course. These results suggest that species within clumps behave in a quasi-neutral state, but even minor shifts in trait composition may affect species biovolume. Our findings point that EN belongs to the plausible mechanisms explaining community assembly in river ecosystems.
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ecology
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SpecHap: a diploid phasing algorithm based on spectral graph theory Haplotype phasing is essential to study diploid eukaryotic organisms. High-throughput sequencing, including next-generation sequencing and third-generation sequencing from different technologies, brings possibilities for haplotype assembly. Although there exist multiple haplotype phasing algorithms, only a few are portable across sequencing technologies with the premise of efficiency and accuracy. Herein, we proposed SpecHap, a novel haplotype assembly tool that leverages spectral graph theory, transforming haplotype phasing into an algebraic problem. On both in silico and whole-genome-sequencing datasets, SpecHap consumed less memory and required less CPU time, yet achieved comparable accuracy comparing to state-of-art methods across all the test instances of next-generation sequencing, linked-reads, high-throughput chromosome conformation capture sequencing, PacBio single-molecule real-time sequencing and Oxford Nanopore long-reads sequencing data. Furthermore, SpecHap successfully phased an individual Ambystoma mexicanumm, a species with gigantic diploid genomes, within 6 CPU hours and 945MB peak memory usage, while other tools failed to yield results either due to a memory overflow (40GB) or a time limit excess (5 days). Our results demonstrated that SpecHap is scalable, efficient and accurate for diploid phasing, supporting diverse sequencing platforms.
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bioinformatics
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Comparative proximity biotinylation implicates RAB18 in cholesterol mobilization and biosynthesis Loss of functional RAB18 causes the autosomal recessive condition Warburg Micro syndrome. To better understand this disease, we used proximity biotinylation to generate an inventory of potential RAB18 effectors. A restricted set of 25 RAB18- interactions were dependent on the binary RAB3GAP1-RAB3GAP2 RAB18-guanine nucleotide exchange factor (GEF) complex. Consistent with a role for RAB18 in regulating membrane contact sites (MCSs), interactors included groups of microtubule/membrane-remodelling proteins, membrane-tethering and docking proteins, and lipid-modifying/transporting proteins. We provide direct evidence validating novel interactions with SEC22A and TMCO4. We also provide functional evidence supporting identified interactions with OSBPL2/ORP2, INPP5B and the {Delta}8-{Delta}7 sterol isomerase emopamil binding protein (EBP). Notably, the cholesterol precursor and EBP-product lathosterol accumulates in RAB18-null cells. Moreover, de novo cholesterol biosynthesis is impaired in cells in which RAB18 is absent or dysregulated. Our data demonstrate that GEF-dependent Rab-interactions are highly amenable to interrogation by proximity biotinylation and may suggest that Micro syndrome is a cholesterol biosynthesis disorder.
SUMMARY STATEMENTWe used proximity biotinylation together with guanine nucleotide exchange factor (GEF)-null cell lines to discriminate functional RAB18-interactions. Our subsequent functional work suggests RAB18 activity influences cholesterol biosynthesis.
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cell biology
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The Euler Characteristic and Topological Phase Transitions in Complex Systems In this work, we use methods and concepts of applied algebraic topology to comprehensively explore the recent idea of topological phase transitions (TPT) in complex systems. TPTs are characterized by the emergence of nontrivial homology groups as a function of a threshold parameter. Under certain conditions, one can identify TPTs via the zeros of the Euler characteristic or by singularities of the Euler entropy. Recent works provide strong evidence that TPTs can be interpreted as a complex networks intrinsic fingerprint. This work illustrates this possibility by investigating some classic network and empirical protein interaction networks under a topological perspective. We first investigate TPT in protein-protein interaction networks (PPIN) using methods of topological data analysis for two variants of the Duplication-Divergence model, namely, the totally asymmetric model and the heterodimerization model. We compare our theoretical and computational results to experimental data freely available for gene co-expression networks (GCN) of Saccharomyces cerevisiae, also known as bakers yeast, as well as of the nematode Caenorhabditis elegans. Supporting our theoretical expectations, we can detect topological phase transitions in both networks obtained according to different similarity measures. Later, we perform numerical simulations of TPTs in four classical network models: the Erd[o]s-Renyi model, the Watts-Strogatz model, the Random Geometric model, and the Barabasi-Albert. Finally, we discuss some perspectives and insights on the topic. Given the universality and wide use of those models across disciplines, our work indicates that TPT permeates a wide range of theoretical and empirical networks.
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biophysics
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Predicting transmembrane protein-protein complexes: TransINT, a novel computational approach Because of their considerable number and diversity, membrane proteins and their macromolecular complexes represent the functional units of cells. Their quaternary structure may be stabilized by interactions between the -helices of different proteins in the hydrophobic region of the cell membrane. Membrane proteins also represent potential pharmacological targets par excellence for various diseases. Unfortunately, their experimental 3D structure and that of their complexes with intramembrane interacting partners are scarce due to technical difficulties. To overcome this key problem, we devised PPIMem, a computational approach for the specific prediction of higher-order structures of -helical transmembrane proteins. The novel approach involves identification of the amino acid residues at the interface of complexes with a 3D structure. The identified residues compose then interaction motifs that are conveniently expressed as mathematical regular expressions. These are used for motif search in databases, and for the prediction of intramembrane protein-protein complexes. Our template interface-based approach predicted 21, 544 binary complexes between 1, 504 eukaryotic plasma membrane proteins across 39 species. We compared our predictions to experimental datasets of protein-protein interactions as a first validation method. The PPIMem online database with the annotated predicted interactions is implemented as a web server and can be accessed directly at https://transint.shinyapps.io/transint/.
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bioinformatics
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Disentangling spatial and environmental effects: flexible methods for community ecology and macroecology Community ecologists and macroecologists have long sought to evaluate the importance of environmental conditions in determining species distributions, community composition, and diversity across sites. Different methods have been used to estimate species-environment relationships, but their differences to jointly fit and disentangle spatial autocorrelation and structure remain poorly studied. We compared how methods in four broad families of statistical models estimated the contribution of the environment and space to variation in species binary occurrence and abundance. These methods included distance-based regression, generalized linear models (GLM, and the special case of RDA), generalized additive models (GAM), and tree-based machine learning (ML): regression trees, boosted regression trees (BRT), and random forests. The spatial component of the model consisted of spatial distance (in distance-based regression), Morans Eigenvector Maps (MEM; in GLM and ML), smooth spatial splines (in GAM), or tree-based non-linear modelling of spatial coordinates (in ML). We simulated typical site-by-species data to assess the methods performance in (1) fitting environmental and spatial models, and (2) partitioning the variation explained by environmental and spatial predictors. We observed marked differences in performance mostly caused by imbalanced performance in estimating environmental and spatial effects. Such differences also manifested when analyzing eight different empirical datasets. GLM and BRT with MEMs were generally the most reliable methods for partitioning the variation explained by environmental and spatial effects across a wide range of simulated scenarios. The remaining methods tended to underfit simulated spatial structures, causing underestimation of spatial fractions of variation. Our results suggest that previously overlooked methods for performing variation partitioning, especially tree-based ML, offer flexible approaches to analyze site-by-species matrices. We provide general guidelines on the usefulness of different models under different ecological and sampling scenarios, for species distribution modelling, community ecology, and macroecology.
|
ecology
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Framework to simulate gene regulatory networks with stochastic molecular kinetics and to infer steady-state network structure BackgroundThe temporal progression of many fundamental processes in cells and organisms, including homeostasis, differentiation and development, are governed by gene regulatory networks (GRNs). GRNs balance fluctuations in the output of their genes, which trace back to the stochasticity of molecular interactions. Although highly desirable to understand life processes, predicting the temporal progression of gene products within a GRN is challenging when considering stochastic events such as transcription factor - DNA interactions or protein production and degradation.
ResultsWe report CaiNet, a fast computer-aided interactive network simulation environment optimized to set up, simulate and infer GRNs at molecular detail. In our approach, we consider each network element to be isolated from other elements during small time intervals, after which we synchronize molecule numbers between all network elements. Thereby, the temporal behaviour of network elements is decoupled and can be treated by local stochastic or deterministic solutions. We demonstrate the working principle of the modular approach of CaiNet with a repressive gene cascade comprising four genes. By considering a deterministic time evolution within each time interval for all elements, our method approaches the solution of the system of deterministic differential equations associated with the GRN. By allowing genes to stochastically switch between on and off states or by considering stochastic production of gene outputs, we are able to include increasing levels of stochastic detail and approximate the solution of a Gillespie simulation. Notably, our modular approach further allows for a simple consideration of deterministic delays. We further infer relevant regulatory connections and steady-state parameters of a GRN of up to ten genes from steady-state measurements by identifying each gene of the network with a single perceptron in an artificial neuronal network and using a gradient decent method originally designed to train recurrent neural networks.
ConclusionCaiNet constitutes a user-friendly framework to simulate GRNs at molecular detail and to infer the topology and steady-state parameters of GRNs. Thus, it should prove helpful to analyze or predict the temporal progression of reaction networks or GRNs in cellular and organismic biology. CaiNet is freely available at https://gitlab.com/GebhardtLab/CaiNet.
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systems biology
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Reward value revealed by auction in rhesus monkeys Economic choice is thought to involve the elicitation of the subjective values of the choice options. Thus far, value estimation in animals has relied upon stochastic choices between multiple options presented in repeated trials and expressed from averages of dozens of trials. However, subjective reward valuations are made moment-to-moment and do not always require alternative options; their consequences are usually felt immediately. Here we describe a Becker-DeGroot-Marschak (BDM) auction-like mechanism that provides more direct and simple valuations with immediate consequences. The BDM encourages agents to truthfully reveal their true subjective value in individual choices (incentive compatibility). Monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices, thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimation methods. The feasibility of BDM bidding in monkeys paves the way for an analysis of subjective neuronal value signals in single trials rather than from averages; the feasibility also bridges the gap to the increasingly used BDM method in human neuroeconomics.
SignificanceThe subjective economic value of rewards cannot be measured directly but must be inferred from observable behavior. Until now, the estimation method in animals was rather complex and required comparison between several choice options during repeated choices; thus, such methods did not respect the imminence of the outcome from individual choices. However, human economic research has developed a simple auction-like procedure that can reveal in a direct and immediate manner the true subjective value in individual choices (Becker-DeGroot-Marschak, BDM, mechanism). The current study implemented this mechanism in rhesus monkeys and demonstrates its usefulness for eliciting meaningful value estimates of liquid rewards. The mechanism allows future neurophysiological assessment of subjective reward value signals in single trials of controlled animal tasks.
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animal behavior and cognition
|
Chr21 protein-protein interactions: enrichment in products involved in intellectual disabilities, autism and Late Onset Alzheimer Disease Intellectual disability (ID) found in Down syndrome (DS), which is characterized by an extra copy of 234 genes on Chr21 is poorly understood. We first used two DS mouse models that either display an extra copy of the Dyrk1A gene or of the mouse Chr16 syntenic region. Exome sequencing of transcripts deregulated in embryonic hippocampus uncovers enrichment in genes involved in chromatin and synapse respectively. Using large-scale yeast two-hybrid screen (154 distinct screens) of human brain library containing at least 107 independent fragments, we identified 3,636 novel protein-protein interactions with an enrichment of direct interactors of both Chromosome 21(Hsa21) baits and rebounds in ID-related genes. Using proximity ligation assays, we identified that Hsa21-encoded proteins are located at the dendritic spine postsynaptic density in a protein network located at the dendritic spine post synapse. We located Hsa21 DYRK1A and DSCAM that confers a [~] 20-fold increase in Autism Spectrum Disorders (ASDs), in this postsynaptic network. We found that a DSCAM intracellular domain binds either DYRK1A or DLGs that are multimeric scaffolds for the clustering of receptors, ion channels, and associated signaling proteins. The DYRK1A-DSCAM interaction is conserved from drosophila to humans. The identified postsynaptic.network is enriched in ARC-related synaptic plasticity, ASDs and Late-Onset Alzheimer Disease. Altogether, these results emphasize links between DS and brain diseases with complex genetics.
|
neuroscience
|
A modular RNA interference system for multiplexed gene regulation The rational design and realisation of simple-to-use genetic control elements that are modular, orthogonal and robust is essential to the construction of predictable and reliable biological systems of increasing complexity. To this effect, we introduce modular Artificial RNA interference (mARi), a rational, modular and extensible design framework that enables robust, portable and multiplexed post-transcriptional regulation of gene expression in Escherichia coli. The regulatory function of mARi was characterised in a range of relevant genetic contexts, demonstrating its independence from other genetic control elements and the gene of interest, and providing new insight into the design rules of RNA based regulation in E. coli, while a range of cellular contexts also demonstrated it to be independent of growth-phase and strain type. Importantly, the extensibility and orthogonality of mARi enables the simultaneous post-transcriptional regulation of multi-gene systems as both single-gene cassettes and poly-cistronic operons. To facilitate adoption, mARi was designed to be directly integrated into the modular BASIC DNA assembly framework. We anticipate that mARi-based genetic control within an extensible DNA assembly framework will facilitate metabolic engineering, layered genetic control, and advanced genetic circuit applications.
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synthetic biology
|
Helping those who help others for indirect fitness benefits not indirect reciprocity Helping those who help others appears to be a widespread phenomenon. It is typically framed as indirect reciprocity in which individuals who are seen to help later receive returns from third parties. However, indirect reciprocity only works when individuals condition their help not just on how their recipient has behaved in the past but also on whether their recipient was justified in behaving that way. It also requires sufficient repeated interactions of this type among other individuals for a benefit to be reciprocated. These factors limit the scope of indirect reciprocity to explain cases where people do help those who help others. Here, I propose instead that helping can be explained by the indirect fitness benefits (or relatedness) that result from helping other helpers in groups. This means that when individuals help other helpers, they may not make any returns via indirect reciprocity, but rather they may be helping a strategy of helping those who help. In this way, the helping strategy can spread even when helping has no net benefit to the individual helper. This is a form of relatedness in which individuals help their kin that are recognized by their helping behaviour. As such, conditional helping is likely to be found where population structure promotes relatedness through non-random association. The analysis suggests indirect reciprocity may not have played the decisive role in the evolution of human cooperation that is often thought, but paradoxically that the use of image scores deserves renewed attention as a strategy of helping those with the same behaviour.
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evolutionary biology
|
Modeling uniquely human gene regulatory function in humanized mice The evolution of uniquely human traits likely entailed changes in developmental gene regulation. Human Accelerated Regions (HARs), which include transcriptional enhancers harboring a significant excess of human-specific sequence changes, are leading candidates for driving gene regulatory modifications in human development. However, insight into whether HARs alter the level, distribution and timing of endogenous gene expression remains limited. We examined the role of the HAR HACNS1 (HAR2) in human evolution by interrogating its molecular functions in a humanized mouse model. We find that HACNS1 maintains its human-specific enhancer activity in humanized mice and that it modifies expression of Gbx2, which encodes a homeobox transcription factor, during limb development. Using single-cell RNA-sequencing, we demonstrate that Gbx2 is upregulated in the chondrogenic mesenchyme of humanized limbs, supporting that HACNS1 alters gene expression in cell types involved in skeletal patterning. Our findings illustrate that humanized mouse models provide mechanistic insight into how HARs modified gene expression in human evolution.
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genomics
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Electron transfer proteins in gut bacteria yield metabolites that circulate in the host It has long been known that proteolytic Clostridia obtain their energy by coupling oxidative and reductive pathways for amino acid metabolism - the Stickland reaction1. The oxidation of one amino acid is coupled with reduction of another, yielding energy in the former step and re-achieving redox balance with the latter. Here, we find that the gut bacterium, Clostridium sporogenes metabolizes amino acids through reductive pathways to produce metabolites that circulate within the host. Measurements in vitro indicate that reductive Stickland pathways are coupled to ATP formation, revealing their role in energy capture by gut bacteria. By probing the genetics of C. sporogenes, we find that the Rnf complex is involved in reductive amino acid metabolism. Rnf complex mutants are attenuated for growth in the mouse gut, demonstrating the importance of energy capture during reductive metabolism for gut colonization. Our findings reveal that the production of high-abundance molecules by a commensal bacterium within the host gut is linked to an energy yielding redox process.
|
microbiology
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Integration of immunome with disease-gene network reveals common cellular mechanisms between IMIDs and drug repurposing strategies ObjectiveDevelopment and progression of immune-mediated inflammatory diseases (IMIDs) involve intricate dysregulation of the disease associated genes (DAGs) and their expressing immune cells. Due to the complex molecular mechanism, identifying the top disease associated cells (DACs) in IMIDs has been challenging. Here, we aim to identify the top DACs and DAGs to help understand the cellular mechanism involved in IMIDs and further explore therapeutic strategies.
MethodUsing transcriptome profiles of 40 different immune cells, unsupervised machine learning, and disease-gene networks, we constructed the Disease-gene IMmune cell Expression (DIME) network, and identified top DACs and DAGs of 12 phenotypically different IMIDs. We compared the DIME networks of IMIDs to identify common pathways between them. We used the common pathways and publicly available drug-gene network to identify promising drug repurposing targets.
ResultWe found CD4+Treg, CD4+Th1, and NK cells as top DACs in the inflammatory arthritis such as ankylosing spondylitis (AS), psoriatic arthritis, and rheumatoid arthritis (RA); neutrophils, granulocytes and BDCA1+CD14+ cells in systemic lupus erythematosus and systemic scleroderma; ILC2, CD4+Th1, CD4+Treg, and NK cells in the inflammatory bowel diseases (IBDs). We identified lymphoid cells (CD4+Th1, CD4+Treg, and NK) and their associated pathways to be important in HLA-B27 type diseases (psoriasis, AS, and IBDs) and in primary-joint-inflammation-based inflammatory arthritis (AS and RA). Based on the common cellular mechanisms, we identified lifitegrast as potential drug repurposing candidate for Crohns disease, and other IMIDs.
ConclusionOur method identified top DACs, DAGs, common pathways, and proposed potential drug repurposing targets between IMIDs. To extend our method to other diseases, we built the DIME tool. Thus paving way for future (pre-)clinical research.
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bioinformatics
|
Cavefish cope with environmental hypoxia by developing more erythrocytes and overexpression of hypoxia inducible genes Dark caves lacking primary productivity can expose subterranean animals to hypoxia. We used the surface-dwelling (surface fish) and cave-dwelling (cavefish) morphs of Astyanax mexicanus as a model for understanding the mechanisms of hypoxia tolerance in the cave environment. Primitive hematopoiesis, which is restricted to the posterior lateral mesoderm in other teleosts, also occurs in the anterior lateral mesoderm in Astyanax, potentially pre-adapting surface fish for hypoxic cave colonization. Cavefish have enlarged both hematopoietic domains and develop more erythrocytes than surface fish, which are required for normal development in both morphs. Laboratory induced hypoxia suppresses growth in surface fish but not in cavefish. Both morphs respond to hypoxia by overexpressing Hypoxia-Inducible Factor (HIF) pathway genes, but some hif genes are constitutively upregulated in normoxic cavefish to similar levels as hypoxic surface fish. We conclude that cavefish cope with hypoxia by increasing erythrocyte development and constitutive HIF gene overexpression.
SummaryAstyanax mexicanus cavefish cope with hypoxic environments by expanding embryonic hematopoietic domains, increasing the capacity for erythrocyte development, and constitutive overexpression of hypoxia-inducible genes.
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developmental biology
|
Combining Focal-ERG, Fluorescein Angiography, and SD-OCT for Retinal Neurovascular Analysis in a Mouse OIR-Model. The development of non-invasive live ocular imaging and electrophysiological test systems for rodent eyes provides new tools for not only averaged analysis of the entire retina but also the ability to see, test, and compare different subregions of the same retina. These new capabilities provide the possibility for more detailed examinations of local structural and functional relationships within a single eye and the ability to also follow changes longitudinally over time. We have developed protocols based around the Micron-III/IV retinal imaging camera system for combining fluorescent imaging of the neural retinal micro-vasculature by FA (fluorescein angiography), imaging of all neural retinal layers by SD-OCT (Spectral-Domain Ocular Coherence Tomography), and focal "spot" light-targeted electroretinography (Focal-ERG) to relate the local neurovascular unit structure to the inner (photoreceptor) and outer-retinal electrical response to light stimulation. For demonstration purposes we have used the popular mouse oxygen induced retinopathy (OIR) model, which causes radial central patches of retinal neuron loss mostly in zones away from and between the primary retinal arteries and veins. In this model, the loss of central microvasculature is induced developmentally in mouse litters exposed to 75% oxygen from age P7 to P11. Return to room air on P12, causes several days of retinal ischemia during which neurons, mostly of the inner retina, perish. Bipolar and ganglion cell death ends as neovascular growth revascularizes the central retina. This model provides for non-uniform retinal damage as well as gradual progression and resolution over time. The OIR model was used to generate regions of inner retinal neuron loss in B6.Cg-TgThy1-YFP mice. Using image-guided focal-ERG, the dark-adapted mixed rod-cone light response was compared using stimulation of small circular (0.27 mm diameter) target areas located in the central retinas of the same eyes (OIR and control). The same areas of the same retinas were followed over three ages after revascularization (P21, P28 and P42).
ConclusionsCombined FA and SD-OCT imaging can provide local geographic specific information on retinal structural changes and be used to select different retinal areas within the same eye for testing of local light response. This analysis strategy can be employed for studies with rodent disease models that do not uniformly impact the entire retinal area. Combining these techniques would also be useful for testing gene and cell replacement therapies in retinal degeneration models where typically a small zone of the retina is treated. Both treated and untreated retinal zones within the eye can be followed non-invasively over many weeks.
SUMMARYMouse models utilized for retinal disease research including retinal vascular models can display nonuniform changes over the entire retina. Damage or loss of retinal layers and retinal neurons due to hypoxia can impact some retinal areas while leaving adjacent regions unaltered. Combining vascular imaging by fluoresceine angiography, vascular imaging and retinal layer imaging by SD-OCT, and focal-ERG provides us with new tools to examine retinal structure-function relationships within a single retina.
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neuroscience
|
Unconventional kinetochore kinases KKT2 and KKT3 have unique centromere localization domains Chromosome segregation in eukaryotes is driven by the kinetochore, the macromolecular protein complex that assembles onto centromeric DNA and binds spindle microtubules. Cells must tightly control the number and position of kinetochores so that all chromosomes assemble a single kinetochore. A central player in this process is the centromere-specific histone H3 variant CENP-A, which localizes constitutively at centromeres and promotes kinetochore assembly. However, CENP-A is absent from several eukaryotic lineages including kinetoplastids, a group of evolutionarily divergent eukaryotes that have an unconventional set of kinetochore proteins. There are six proteins that localize constitutively at centromeres in the kinetoplastid parasite Trypanosoma brucei, among which two homologous protein kinases (KKT2 and KKT3) have limited similarity to polo-like kinases. In addition to the N-terminal kinase domain and the C-terminal divergent polo boxes, KKT2 and KKT3 have a central domain of unknown function as well as putative DNA-binding motifs. Here we show that KKT2 and KKT3 are important for the localization of several kinetochore proteins and that their central domains are sufficient for centromere localization in T. brucei. Crystal structures of the KKT2 central domain from two divergent kinetoplastids reveal a unique zinc-binding domain (termed the CL domain for centromere localization), which promotes its kinetochore localization in T. brucei. Mutations in the equivalent domain in KKT3 abolish its kinetochore localization and function. Our work shows that the unique central domains play a critical role in mediating the centromere localization of KKT2 and KKT3.
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cell biology
|
Deriving Ranges of Optimal Estimated Transcript Expression Due to Non-identifiability Current expression quantification methods suffer from a fundamental but under-characterized type of error: the most likely estimates for transcript abundances are not unique. This means multiple estimates of transcript abundances generate the observed RNA-seq reads with equal likelihood, and the underlying true expression cannot be determined. This problem is called non-identifiability for probabilistic models, and is further exacerbated by incomplete reference transcriptome. That is, reads may be sequenced from unannotated expressed transcripts. Graph quantification is a generalization to transcript quantification, accounting for the reference incompleteness by allowing exponentially many unannotated transcripts to express reads. We propose methods to calculate a "confidence range of expression" for each transcript, representing its possible abundance across equally optimal estimates for both quantification models. This range informs both whether a transcript has potential estimation error due to non-identifiability and the extent of the error. Applying our methods to the Human Body Map data, we observe 35%-50% of transcripts potentially suffer from inaccurate quantification caused by non-identifiability. When comparing the expression between isoforms in one sample, we find that the degree of inaccuracy of 20%-47% transcripts can be so large that the ranking of expression between the transcript and its sibling isoforms cannot be determined. When comparing the expression of a transcript between two groups of RNA-seq samples in differential expression analysis, we observe that the majority of detected differentially expressed transcripts are reliable with a few exceptions after considering the ranges of the optimal expression estimates. The code for computing the range of expression is available at https://github.com/Kingsford-Group/subgraphquant. The code for the involved analyses is available at https://github.com/Kingsford-Group/subgraphquantanalysis.
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bioinformatics
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SEC is an anti-angiogenic virulence factor that promotes Staphylococcus aureus Infective Endocarditis Independent of Superantigen Activity The superantigen staphylococcal enterotoxin C (SEC) is critical for Staphylococcus aureus infective endocarditis (SAIE) in rabbits. Superantigenicity, its hallmark function, was proposed to be a major underlying mechanism driving SAIE but was not directly tested. With the use of S. aureus MW2 expressing SEC toxoids, we show that superantigenicity does not sufficiently account for vegetation growth, myocardial inflammation, and acute kidney injury in the rabbit model of native valve SAIE. These results highlight the critical contribution of an alternative function of superantigens to SAIE. In support of this, we provide evidence that SEC exerts anti-angiogenic effects by inhibiting branching microvessel formation in an ex vivo rabbit aortic ring model and by inhibiting endothelial cell expression of one of the most potent mediators of angiogenesis, VEGF-A. SECs ability to interfere with tissue re-vascularization and remodeling after injury serves as a mechanism to promote SAIE and its life-threatening systemic pathologies.
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microbiology
|
HIV corruption of the Arp2/3-Cdc42-IQGAP1 axis to hijack cortical F-Actin to promote cell-cell viral spread. F-Actin remodelling is important for the spread of HIV via cell-cell contacts, yet the mechanisms by which HIV corrupts the actin cytoskeleton are poorly understood. Through live cell imaging and focused ion beam scanning electron microscopy (FIB-SEM), we observed F-Actin structures that exhibit strong positive curvature to be enriched for HIV buds. Virion proteomics, gene silencing, and viral mutagenesis supported a Cdc42-IQGAP1-Arp2/3 pathway as the primary intersection of HIV budding, membrane curvature and F-Actin regulation. Whilst HIV egress activated the Cdc42-Arp2/3 filopodial pathway, this came at the expense of cell-free viral release. Importantly, release could be rescued by cell-cell contact, provided Cdc42 and IQGAP1 were present. From these observations we conclude that a proportion out-going HIV has corrupted a central F-Actin node that enables initial coupling of HIV buds to cortical F-Actin to place HIV at the leading cell edge. Whilst this initially prevents particle release, maturation of cell-cell contacts signals back to this F-Actin node to enable viral release & subsequent infection of the contacting cell.
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microbiology
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Cortical control of virtual self-motion using task-specific subspaces Brain-machine interfaces (BMIs) for reaching have enjoyed continued performance improvements, yet there remains significant need for BMIs that control other movement classes. Recent scientific findings suggest that the intrinsic covariance structure of neural activity depends strongly on movement class, potentially necessitating different decode algorithms across classes. To address this, we developed a self-motion BMI based on cortical activity as monkeys performed non-reaching arm movements: cycling a hand-held pedal to progress along a virtual track. Unlike during reaching, we found no high-variance dimensions that directly correlated with to-be-decoded variables. Yet we could decode a single variable - self-motion - by non-linearly leveraging structure that spanned many high-variance neural dimensions. Resulting online BMI-control success rates approached those during manual control. These findings make two broad points regarding how to build decode algorithms that harmonize with the empirical structure of neural activity in motor cortex. First, even when decoding from the same cortical region (e.g., arm-related motor cortex) different movement classes may need to employ very different strategies. Although correlations between neural activity and hand velocity are prominent during reaching tasks, they are not a fundamental property of motor cortex and cannot be counted on to be present in general. Second, although one generally desires a low-dimensional readout, it can be beneficial to leverage a multi-dimensional high-variance subspace. Fully embracing this approach requires highly non-linear approaches tailored to the task at hand, but can produce near-native levels of performance.
Significance StatementMany BMI decoders have been constructed for controlling movements normally performed with the arm. Yet it is unclear how these will function beyond the reach-like scenarios where they were developed. Existing decoders implicitly assume that neural covariance structure, and correlations with to-be-decoded kinematic variables, will be largely preserved across tasks. We find that the correlation between neural activity and hand kinematics, a feature typically exploited when decoding reach-like movements, is essentially absent during another task performed with the arm: cycling through a virtual environment. Nevertheless, the use of a different strategy, one focused on leveraging the highest-variance neural signals, supported high performance real-time BMI control.
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neuroscience
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Spergulin-A strives intra-macrophage leishmanicidal activity by regulating the host P2X7R-P38MAPK axis Current drugs are inadequate for the treatment of visceral leishmaniasis an immunosuppressive ailment caused by Leishmania donovani. Regrettably, there is no plant-origin antileishmanial drug present. P2X7R is constitutively present on macrophage surfaces and can be a putative therapeutic target in intra-macrophage pathogens with function attributes towards inflammation, host cell apoptosis, altered redox, and phagolysosomal maturation by activating p38MAPK. Here we demonstrated that the initial interaction of Spergulin-A (SpA), a triterpenoid saponin with RAW 264.7 macrophages was mediated through P2X7R involving the signaling cascade intermediates Ca++, P38MAPK, and NF-{kappa}{beta}. P38MAPK involvement is shown to have specific and firm importance in leishmanial killing with increased NF-{kappa}Bp65. Phago-lysosomal maturation by Sp A also campaigns for another contribution of P2X7R. In vivo evaluation of the anti-leishmanial activity of Sp A was monitored through expression analyses of P2X7R, P38MAPK, and NF-{kappa}{beta} in murine spleen and bone-marrow macrophages and advocated Sp A of being a natural compound of leishmanicidal functions which acted through the P2X7R-P38MAPK axis.
SIGNIFICANCE OR IMPORTANCEPreciously, this manuscript demonstrated previously unreported initial interaction of Spergulin-A, a triterpenoid saponin isolated from Glinus oppositifolius with macrophages through P2X7R involving the signaling cascade intermediates Ca++, P38MAPK, and NF-{kappa}{beta}. Signaling interaction is shown to have specific importance in the leishmanial killing. Phago-lysosomal maturation also campaigns for another contribution of P2X7R. In vivo evaluation was monitored through P2X7R, P38MAPK, and NF-{kappa}{beta} in murine spleen and bone-marrow macrophages and advocated Sp A of being a natural compound of leishmanicidal functions which acted through the P2X7R-P38MAPK axis. The result supports that Spergulin-A can provide new lead molecules for the development of alternative drugs against VL. We feel very strongly that this work can be very interesting as it describes a detailed evaluation of leishmanicidal effect by Sp A and thus has every potential to attract a lot of workers especially in the fields of pharmacology, drug development, immunology, as well as parasitology.
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molecular biology
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Is N-Hacking Ever OK? A Simulation-based study After an experiment has been completed and analyzed, a trend may be observed that is "not quite significant". Sometimes in this situation, researchers incrementally grow their sample size N in an effort to achieve statistical significance. This is especially tempting in situations when samples are very costly or time-consuming to collect, such that collecting an entirely new sample larger than N (the statistically sanctioned alternative) would be prohibitive. Such post- hoc sampling or "N-hacking" is denounced because it leads to an excess of false positive results. Here simulations are used to illustrate and explain how unplanned incremental sampling causes excess false positives. In a parameter regime representative of practice in many research fields, however, simulations show that the inflation of the false positive rate is surprisingly modest. The effect on false positive rate is only half the story. What many researchers really care about is the effect of N-hacking on the likelihood that a positive result is a real effect: the positive predictive value (PPV). This question has not been considered in the reproducibility literature. The answer depends on the effect size and the prior probability of an effect. Although in practice these values are not known, simulations show that for a wide range of values, the PPV of results obtained by N-hacking is in fact higher than that of non-incremented experiments of the same sample size and statistical power. This is because the increase in false positives is more than offset by the increase in true positives. Therefore, in many situations, adding a few samples to shore up a nearly-significant result would in fact increase reproducibility, counter to current rhetoric. To strictly control the false positive rate on the null hypothesis, the sampling plan (and all other study details) must be prespecified. But if this is not the primary concern, as in exploratory studies, collecting additional samples to resolve a borderline p value can confer previously unappreciated advantages for efficiency the positive predictive value of the generated hypotheses.
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scientific communication and education
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Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: A software engineering perspective Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context can be challenging due to an inflexible monolithic structure, confusing code, missing documentation or other issues. These challenges are very similar to those faced in the engineering of large software systems. It is therefore likely that addressing model design at the software engineering level will also be beneficial in systems biology. To do this, researchers cannot just rely on using an accepted standard language. They need to be aware of the characteristics that make this language desirable and they need guidelines on how to utilize them to make their models more reproducible, understandable, reusable, and extensible. Drawing upon our experience with translating and extending a model of the human baroreflex, we therefore propose a list of desirable language characteristics and provide guidelines and examples for incorporating them in a model: In our opinion, a mathematical modeling language used in systems biology should be modular, human-readable, hybrid (i.e., support multiple formalisms), open, declarative, and support the graphical representation of models. We compare existing modeling languages with respect to these characteristics and show that there is no single best language but that trade-offs always have to be considered. We also illustrate the benefits of the individual language characteristics by translating a monolithic model of the human cardiac conduction system to a modular version using the modeling language Modelica as an example. Our experiment can be seen as emblematic for model reuse in a multi-scale setting. It illustrates how each characteristic, when applied consistently, can facilitate the reuse of the resulting model. We therefore recommend that modelers consider these criteria when choosing a programming language for any biological modeling task and hope that our work sparks a discussion about the importance of software engineering aspects in mathematical modeling languages.
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systems biology
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Amyloid-like aggregates cause lysosomal defects in neurons via gain-of-function toxicity The autophagy-lysosomal pathway is impaired in many neurodegenerative diseases characterized by protein aggregation, but the link between aggregation and lysosomal dysfunction remains poorly understood. Here, we combine cryo-electron tomography, proteomics and cell biology studies to investigate the effects of protein aggregates in primary neurons. We use artificial amyloid-like {beta}-sheet proteins ({beta} proteins) to focus on the gain-of-function aspect of aggregation. These proteins form fibrillar aggregates and cause neurotoxicity. We show that late stages of autophagy are impaired by the aggregates, resulting in lysosomal alterations reminiscent of lysosomal storage disorders. Mechanistically, {beta} proteins interact with and sequester AP-31, a subunit of the AP-3 adaptor complex involved in protein trafficking to lysosomal organelles. This leads to destabilization of the AP-3 complex, missorting of AP-3 cargo, and lysosomal defects. Restoring AP-31 expression ameliorates neurotoxicity caused by {beta} proteins. Altogether, our results highlight the link between protein aggregation and neurotoxicity, pointing to lysosomes as particularly vulnerable organelles.
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cell biology
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Use of the p-value as a size-dependent function to address practical differences when analyzing large datasets Biomedical research has come to rely on p-values as a deterministic measure for data-driven decision making. In the largely extended null-hypothesis significance testing (NHST) for identifying statistically significant differences among groups of observations, a single p-value computed from sample data is routinely compared with a threshold, commonly set to 0.05, to assess the evidence against the hypothesis of having non-significant differences among groups, or the null hypothesis. Because the estimated p-value tends to decrease when the sample size is increased, applying this methodology to large datasets results in the rejection of the null hypothesis, making it not directly applicable in this specific situation. Herein, we propose a systematic and easy-to-follow method to detect differences based on the dependence of the p-value on the sample size. The proposed method introduces new descriptive parameters that overcome the effect of the size in the p-value interpretation in the framework of large datasets, reducing the uncertainty in the decision about the existence of biological/clinical differences between the compared experiments. This methodology enables both the graphical and quantitative characterization of the differences between the compared experiments guiding the researchers in the decision process. An in-depth study of the proposed methodology is carried out using both simulated and experimentally obtained data. Simulations show that under controlled data, our assumptions on the p-value dependence on the sample size holds. The results of our analysis in the experimental datasets reflect the large scope of this approach and its interpretability in terms of common decision-making and data characterization tasks. For both simulated and real data, the obtained results are robust to sampling variations within the dataset.
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bioinformatics
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Foster thy young: Enhanced prediction of orphan genes in assembled genomes Proteins encoded by newly-emerged genes ("orphan genes") share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene annotation pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes and 99% of ancient genes in Arabidopsis. We provide a light weight, flexible, reproducible solution to improve gene prediction.
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bioinformatics
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Offline tDCS modulates prefrontal cortical-subcortical cerebellar fear pathways in delayed fear extinction Transcranial direct current stimulation (tDCS) has been studied to enhance extinction-based treatments for anxiety disorders. However, the field shows conflicting results about the anxiolytic effect of tDCS and only a few studies have previously observed the extinction of consolidated memories.
Off-line tDCS modulates subsequent fear response (fear recall and fear extinction) neural activity and connectivity, throughout changes in the fear pathway that is critically involved in the pathogenesis of anxiety disorders.
Thirty-four women participated in a two-day fear conditioning procedure. On day 1, women were randomly assigned to the control group (n=18) or the tDCS group (n=16) and went through a fear acquisition procedure. On day 2, the tDCS group received 20min tDCS at 1mA [cathode - F4; anode - contralateral deltoid] immediately before extinction and while inside the MRI scanner. The control group completed the extinction procedure only.
fMRI whole brain contrast analysis showed stimulation dependent activity patterns with the tDCS group showing decreased neural activity during the processing of the CS+ and increased activity during the processing of the CS, in prefrontal, postcentral and paracentral regions, during late extinction. PPI analysis showed tDCS impact on the connectivity between the left dorsolateral prefrontal cortex and three clusters along the cortical-amygdalo-hippocampal- cerebellar pathway, during the processing of the CS+ in late extinction (TFCE corrected at p <.05).
The increased neuronal activity during the processing of safety cues and the stronger coupling during the processing of threat cues might well be the mechanisms by which tDCS contributes to stimuli discrimination.
HighlightsO_LIThe anxiolytic effect of cathodal tDCS is controversial.
C_LIO_LIWe show cathodal tDCS modulatory effect on delayed extinction of the fear response.
C_LIO_LICathodal tDCS modulates the processing of safe and threatening cues.
C_LIO_LICathodal tDCS modulates the activity and connectivity of the fear network.
C_LI
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neuroscience
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Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases Summary ParagraphCommon human diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1-3. Polygenic scores (PGSs) aggregate these alleles into a metric which represents an individuals genetic predisposition to a specific disease. PGSs have shown promise for early risk prediction4-7, and there is potential to use PGSs to understand disease biology in parallel8. Here, we investigate the role plasma protein levels play in cardiometabolic disease risk in a cohort of 3,087 healthy individuals using PGSs. We found PGSs for coronary artery disease (CAD), type 2 diabetes (T2D), chronic kidney disease (CKD), and ischaemic stroke (IS) were associated with levels of 49 plasma proteins. These associations were polygenic in architecture, largely independent of cis protein QTLs, and robust to environmental variation. Over a median 7.7 years follow-up, 28 of these plasma proteins were associated with future myocardial infarction (MI) or T2D events, 16 of which were causal mediators between polygenic risk and incident disease. These protein mediators of polygenic disease risk included targets of approved therapies which may have repurposing potential. Our results demonstrate that PGSs can identify proteins with causal roles in disease, and may have utility in drug development.
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genetics
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A role for the locus coeruleus in the modulation of feeding Recent data suggest that LC-NE neurons play a role in fear-induced suppression of feeding, but their endogenous activity in naturally behaving animals has not been explored. We found that endogenous activity of LC-NE neurons was enhanced during food approach and suppressed during food consumption, and that these food-evoked LC-NE responses were attenuated in sated mice. Interestingly, visual-evoked LC-NE activity was also attenuated in sated mice, demonstrating that internal satiety state modulates LC-NE encoding of multiple behavioral states. We also found that food intake could be attenuated by brief or longer durations of LC-NE activation. Lastly, we demonstrated that activation of LC neurons suppresses feeding and enhances avoidance and anxiety-like responding through a projection to the lateral hypothalamus. Collectively, our data suggest that LC-NE neurons modulate feeding by integrating both external cues (e.g., anxiogenic environmental cues) and internal drives (e.g., nutritional state).
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neuroscience
|
Theta activity paradoxically boosts gamma and ripple frequency sensitivity in prefrontal interneurons Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background inputs statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons sensitivity to gamma- and ripple-frequencies. A novel time-resolved dynamic gain analysis revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism presumably contributes substantially to cross-frequency coupling and predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms.
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neuroscience
|
Relationships between community composition, productivity and invasion resistance in semi-natural bacterial microcosms Experiments with artificial communities have suggested that invasion resistance in microbial communities is often a side-effect of community members contribution towards overall community productivity (broadly defined as cumulative cell density and/or growth rate). However, few experiments have investigated this in natural microbial communities. We conducted experimental invasions of two bacterial species (Pseudomonas fluorescens and Pseudomonas putida) into laboratory microcosms inoculated with 680 different mixtures of bacteria derived from naturally-occurring microbial communities collected in the field. Using 16S amplicon sequencing to characterise microcosm starting composition, and high-throughput assays of community phenotypes including productivity and invader survival, we determined that productivity is a key predictor of invasion resistance in natural microbial communities, substantially mediating the effect of composition on invasion resistance. The results suggest that similar general principles govern invasion in artificial and natural communities, and that factors affecting resident community productivity should be a focal point for future microbial invasion experiments.
|
ecology
|
Mismatch responses mediated by adaptation and deviance detection have complementary functional profiles that point to different auditory short-term memory systems Mismatch negativity (MMN) is a macroscopic EEG deflection in response to rare or unexpected sounds. It has provided important insights into auditory short-term memory, pre-attentive guidance of attention, and their alteration in conditions such as schizophrenia. It remains unclear if MMN is caused by passive adaptation, active memory-comparison processes (deviance detection; DD), or a mix of both. To answer this question, macaque monkeys listened to a new paradigm that quantified both components of MMN. Micro- and macroscopic mismatch responses in the rhesus were dominated by adaptation at short latencies but included a smaller contribution of deviance detection at longer latencies. Most importantly, we show that mismatch responses mediated by adaptation have a short temporal scope and narrow frequency tuning while mismatch responses mediated by deviance detection have a longer temporal scope but broader frequency tuning. The different functional profiles point to the involvement of two distinct auditory short-term memory systems and complementary roles in the pre-attentive guidance of attention.
|
neuroscience
|
A neurocomputational model for intrinsic reward Standard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a computational tool that measures the affective value of experiences (e.g., playing a musical instrument without errors). We go on to validate this tool with neural data, using fMRI to measure neural activity in male and female human subjects performing a reinforcement learning task that incorporated periodic ratings of subjective affective state. Learning performance determined level of payment (i.e., extrinsic reward). Crucially, the task also incorporated a skilled performance component (i.e., intrinsic reward) which did not influence payment. Both extrinsic and intrinsic rewards influenced affective dynamics, and their relative influence could be captured in our computational model. Individuals for whom intrinsic rewards had a greater influence on affective state than extrinsic rewards had greater ventromedial prefrontal cortex (vmPFC) activity for intrinsic than extrinsic rewards. Thus, we show that computational modelling of affective dynamics can index the subjective value of intrinsic relative to extrinsic rewards, a computational hedonometer that reflects both behavior and neural activity that quantifies the affective value of experience.
SIGNIFICANCE STATEMENTTraditional economic indicators are increasingly recognized to provide an incomplete picture of what we value as a society. Standard economic approaches struggle to accurately assign values to non-market activities that nevertheless may be intrinsically rewarding, prompting a need for new tools to measure what really matters to individuals. Using a combination of neuroimaging and computational modeling, we show that despite their lack of instrumental value, intrinsic rewards influence subjective affective state and ventromedial prefrontal cortex activity. The relative degree to which extrinsic and intrinsic rewards influence affective state is predictive of their relative impacts on neural activity, confirming the utility of our approach for measuring the affective value of experiences and other non-market activities in individuals.
|
neuroscience
|
Enrichment of Skeletal Stem Cells from Human Bone Marrow Using Spherical Nucleic Acids Human bone marrow (BM) derived stromal cells contain a population of skeletal stem cells (SSCs), with the capacity to differentiate along the osteogenic, adipogenic and chondrogenic lineages enabling their application to clinical therapies. However, current methods, to isolate and enrich SSCs from human tissues remain, at best, challenging in the absence of a specific SSC marker. Unfortunately, none of the current proposed markers, alone, can isolate a homogenous cell population with the ability to form bone, cartilage, and adipose tissue in humans. Here, we have designed DNA-gold nanoparticles able to identify and sort SSCs displaying specific mRNA signatures. The current approach demonstrates the significant enrichment attained in the isolation of SSCs, with potential therein to enhance our understanding of bone cell biology and translational applications.
TABLE OF CONTENTS
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cell biology
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α-Phenylalanyl tRNA synthetase attenuates Notch signaling by competing with Notch through its N-terminal domain The alpha subunit of the cytoplasmic Phenylalanyl tRNA synthetase (-PheRS, FARSA in humans) displays cell growth and proliferation activities and its elevated levels can induce cell fate changes and tumor-like phenotypes that do neither dependent on the canonical function of charging tRNAPhe with phenylalanine nor on stimulating general translation. In intestinal stem cells of Drosophila midguts, -PheRS levels are naturally slightly elevated and human FARSA mRNA levels are elevated in multiple cancers. In the Drosophila midgut model, elevated -PheRS levels caused the accumulation of many additional proliferating cells resembling intestinal stem cells (ISCs) and enteroblasts (EBs). This phenotype resembles partially the tumor-like phenotype described as Notch RNAi phenotype for the same cells. Genetic interactions between -PheRS and Notch suggest that their activities neutralize each other and that elevated -PheRS levels attenuate Notch signaling whether Notch induces differentiation into enterocytes, neuroblast stem cell proliferation, or transcription of a Notch reporter. These non-canonical functions all map to the N-terminal part of -PheRS which accumulates naturally in the intestine. This truncated version of -PheRS (-S) also localizes to nuclei and displays weak sequence similarity to the Notch intracellular domain (NICD), suggesting that -S might compete with the NICD for binding to a common target. Supporting this hypothesis, the tryptophan (W) residue reported to be key for the interaction between the NICD and the Su(H) BTD domain is not only conserved in -PheRS and -S, but also essential for attenuating Notch signaling.
Author SummaryAminoacyl tRNA synthetases charge tRNAs with their cognate amino acid to ensure proper decoding of the genetic code during translation. Independent of its aminoacylation function, the alpha subunit of Drosophila cytoplasmic Phenylalanyl tRNA synthetase (-PheRS, FARSA in humans) has an additional activity that promotes growth and proliferation (Ho et al., 2021). Here we describe that elevated -PheRS levels also induce cell fate changes and tumorous phenotypes in Drosophila midguts. Excessive proliferating cells with stem and progenitor cell characteristics accumulate and the composition of the terminally differentiated cells changes, too. This phenotype together with observed genetic interactions between -PheRS and Notch levels show that -PheRS counteracts Notch signaling in many different tissues and developmental stages. This novel activity of -PheRS maps to its N-terminal part, which is naturally produced. The fragment contains a DNA binding domain, translocates into nuclei, and displays essential similarities to a Notch domain that binds to the downstream transcription factor. This suggests that it might be competing with Notch for binding to a common target. Not only because Notch plays important roles in many tumors, but also because FARSA mRNA levels are considerably upregulated in many tumors, this novel activity deserves more attention for cancer research.
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cell biology
|
Tracking dynamic adjustments to decision making and performance monitoring processes in conflict tasks How we exert control over our decision-making has been investigated using conflict tasks, which involve stimuli containing elements that are either congruent or incongruent. In these tasks, participants adapt their decision-making strategies following exposure to incongruent stimuli. According to conflict monitoring accounts, conflicting stimulus features are detected in medial frontal cortex, and the extent of experienced conflict scales with response time (RT) and frontal theta-band activity in the electroencephalogram (EEG). However, the consequent adjustments to decision processes following response conflict are not well-specified. To characterise these adjustments and their neural implementation we recorded EEG during a modified Flanker task. We traced the time-courses of performance monitoring processes (frontal theta) and multiple processes related to perceptual decision-making. In each trial participants judged which of two overlaid gratings forming a plaid stimulus (termed the S1 target) was of higher contrast. The stimulus was divided into two sections, which each contained higher contrast gratings in either congruent or incongruent directions. Shortly after responding to the S1 target, an additional S2 target was presented, which was always congruent. Our EEG results suggest enhanced sensory evidence representations in visual cortex and reduced evidence accumulation rates for S2 targets following incongruent S1 stimuli. Results of a follow-up behavioural experiment indicated that the accumulation of sensory evidence from the incongruent (i.e. distracting) stimulus element was adjusted following response conflict. Frontal theta amplitudes positively correlated with RT following S1 targets (in line with conflict monitoring accounts). Following S2 targets there was no such correlation, and theta amplitude profiles instead resembled decision evidence accumulation trajectories. Our findings provide novel insights into how cognitive control is implemented following exposure to conflicting information, which is critical for extending conflict monitoring accounts.
|
neuroscience
|
Hippocampus and amygdala fear memory engrams re-emerge after contextual fear relapse The formation and extinction of fear memories represent two forms of learning that each engage the hippocampus and amygdala. How cell populations in these areas contribute to fear relapse, however, remains unclear. Here, we demonstrate that, in male mice, cells active during fear conditioning in the dentate gyrus of hippocampus exhibit decreased activity during extinction and are re-engaged after contextual fear relapse. In vivo calcium imaging reveals that relapse drives population dynamics in the basolateral amygdala to revert to a network state similar to the state present during fear conditioning. Finally, we find that optogenetic inactivation of neuronal ensembles active during fear conditioning in either the hippocampus or amygdala is sufficient to disrupt fear expression after relapse. These results suggest that fear relapse triggers a partial re-emergence of the original fear memory representation, providing new insight into the neural substrates of fear relapse.
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neuroscience
|
The evolutionary origins of extreme halophilic Archaea Interest and controversy surrounding the evolutionary origins of extremely halophilic Archaea has increased in recent years, due to the discovery and characterization of the Nanohaloarchaea and the Methanonatronarchaeia. Initial attempts in explaining the evolutionary placement of the two new lineages in relation to the classical Halobacteria (also referred to as Haloarchaea) resulted in hypotheses that imply the new groups share a common ancestor with the Haloarchaea. However, more recent analyses have led to a shift: the Nanohaloarchaea have been largely accepted as being a member of the DPANN superphylum, outside of the euryarchaeota; while the Methanonatronarchaeia have been placed near the base of the Methanotecta (composed of the class II methanogens, the Halobacteriales, and Archaeoglobales). These opposing hypotheses have far-reaching implications on the concepts of convergent evolution (unrelated groups evolve similar strategies for survival), genome reduction, and gene transfer. In this work, we attempt to resolve these conflicts with phylogenetic and phylogenomic data. We provide a robust taxonomic sampling of Archaeal genomes that spans the Asgardarchaea, TACK Group, euryarchaeota, and the DPANN superphylum. In addition, we assembled draft genomes from seven new representatives of the Nanohaloarchaea from distinct geographic locations. Phylogenies derived from these data imply that the highly conserved ATP synthase catalytic/non-catalytic subunits of Nanohaloarchaea share a sisterhood relationship with the Haloarchaea. We also employ a novel gene family distance clustering strategy which shows this sisterhood relationship is not likely the result of a recent gene transfer. In addition, we present and evaluate data that argue for and against the monophyly of the DPANN superphylum, in particular, the inclusion of the Nanohaloarchaea in DPANN.
Significance StatementMany recent analyses have considered large groups of Bacteria and Archaea composed exclusively of environmentally assembled genomes as deep branching taxonomic groups in their respective domains. These groups display characteristics distinct from other members of their domain, which can attract unrelated lineages into those groups. This manuscript evaluates the case of the Nanohaloarchaea, and their inclusion in the DPANN Archaea, through careful analysis of the genes that compose the core of the Nanohaloarchaea. Analyses without inspection of the genes that compose a phylogenomic marker set increases the potential for the inclusion of artifacts and confuses the tree/web of life. Due to horizontal gene transfer and phylogenetic reconstruction artifacts, the placement of divergent archaeal classes into larger groups remains uncertain.
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microbiology
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Interpretable machine learning models for single-cell ChIP-seq imputation MotivationSingle-cell ChIP-seq (scChIP-seq) analysis is challenging due to data sparsity. High degree of data sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-seq are lacking. We present SIMPA, a scChIP-seq data imputation method leveraging predictive information within bulk data from ENCODE to impute missing protein-DNA interacting regions of target histone marks or transcription factors.
ResultsImputations using machine learning models trained for each single cell, each target, and each genomic region accurately preserve cell type clustering and improve pathway-related gene identification on real data. Results on simulated data show that 100 input genomic regions are already enough to train single-cell specific models for the imputation of thousands of undetected regions. Furthermore, SIMPA enables the interpretation of machine learning models by revealing interaction sites of a given single cell that are most important for the imputation model trained for a specific genomic region. The corresponding feature importance values derived from promoter-interaction profiles of H3K4me3, an activating histone mark, highly correlate with co-expression of genes that are present within the cell-type specific pathways. An imputation method that allows the interpretation of the underlying models facilitates users to gain an even deeper understanding of individual cells and, consequently, of sparse scChIP-seq datasets.
Availability and implementationOur interpretable imputation algorithm was implemented in Python and is available at https://github.com/salbrec/SIMPA
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bioinformatics
|
Dnmt3a knockout in excitatory neurons impairs postnatal synapse maturation and is partly compensated by repressive histone modification H3K27me3 Two epigenetic pathways of repression, DNA methylation and Polycomb repressive complex 2 (PRC2) mediated gene silencing, regulate neuron development and function, but their respective contributions are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. Loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving neurons with an unmethylated, fetal-like epigenomic pattern at -140,000 genomic regions. The PRC2-associated histone modification H3K27me3 increased at many of these sites, partially compensating for the loss of DNA methylation. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.
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neuroscience
|
TENET: Gene network reconstruction using transfer entropy reveals key regulatory factors from single cell transcriptomic data Accurate prediction of gene regulatory rules is important towards understanding of cellular processes. Existing computational algorithms devised for bulk transcriptomics typically require a large number of time points to infer gene regulatory networks (GRNs), are applicable for a small number of genes, and fail to detect potential causal relationships effectively. Here, we propose a novel approach TENET to reconstruct GRNs from single cell RNA sequencing (scRNAseq) datasets. Employing transfer entropy (TE) to measure the amount of causal relationships between genes, TENET predicts large-scale gene regulatory cascades/relationships from scRNAseq data. TENET showed better performance than other GRN reconstructors, in identifying key regulators from public datasets. Specifically from scRNAseq, TENET identified key transcriptional factors in embryonic stem cells (ESCs) and during direct cardiomyocytes reprogramming, where other predictors failed. We further demonstrate that known target genes have significantly higher TE values, and TENET predicted higher TE genes were more influenced by the perturbation of their regulator. Using TENET, we identified and validated that Nme2 is a culture condition specific stem cell factor. These results indicate that TENET is uniquely capable of identifying key regulators from scRNAseq data.
Key PointsO_LITENET measures putative causal relationships between genes using transfer entropy.
C_LIO_LITENET shows outstanding performance in identifying key regulators compared to existing methods.
C_LIO_LITENET can reveal previously uncharacterized regulators.
C_LI
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bioinformatics
|
Single cell transcriptomic analysis identifies Langerhans cells immunocompetency is critical for ability to induce tolerogenic T cells. Human epidermal Langerhans cells (LCs) can coordinate both immunogenic and tolerogenic immune responses, creating an attractive opportunity for immunomodulation strategies. To investigate transcriptional determinants of human primary LC tolerance we applied single cells RNA-sequencing combined with transcriptional network modelling and functional analysis. Unsupervised clustering of single cell transcriptomes revealed that steady-state LCs exist in immature and immunocompetent states, and become fully immunocompetent on migration. Interestingly, LC migration, which has been shown to result in upregulation of the transcription factor IRF4, led in parallel to increased expression of a tolerogenic gene module including IDO1, LGALS1, LAMTOR1 and IL10RA, which translated to efficient induction of regulatory T cells in co-culture assays by immunocompetent LCs. Using protein expression analysis and perturbation with inhibitors, we confirmed the role of IDO1 as a mediator of LC tolerogenic responses induced during LC migration. Computational analysis of regulons and Partial Information Decomposition analyses identified IRF4 as a key driver for LC tolerogenic programmes. The predicted IRF4-regulated genes were confirmed by analysis of CRISPR-Cas9 edited LCs. These findings suggest that efficient priming of tolerogenic responses by LCs requires upregulation of a migration-coupled maturation program which is superimposed with a tolerance-inducing genomic module.
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systems biology
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A dynamic normalization model of temporal attention Vision is dynamic, handling a continuously changing stream of input, yet most models of visual attention are static. Here, we develop a dynamic normalization model of visual temporal attention and constrain it with new psychophysical human data. We manipulated temporal attention-the prioritization of visual information at specific points in time-to a sequence of two stimuli separated by a variable time interval. Voluntary temporal attention improved perceptual sensitivity only over a specific interval range. To explain these data, we modeled voluntary and involuntary attentional gain dynamics. Voluntary gain enhancement took the form of a limited resource over short time intervals, which recovered over time. Taken together, our theoretical and experimental results formalize and generalize the idea of limited attentional resources across space at a single moment to limited resources across time at a single location.
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neuroscience
|
Multimodal Learning of Pheromone Locations Memorizing pheromonal locations is critical for many mammalian species as it involves finding mates and avoiding competitors. In rodents, pheromonal information is perceived by the main and accessory olfactory systems. However, the role of somatosensation in context dependent learning and memorizing of pheromone locations remains unexplored. We addressed this problem by training female mice on a multimodal task to locate pheromones by sampling volatiles emanating from male urine through the orifices of varying dimensions or shapes that are sensed by their vibrissae. In this novel pheromone location assay, female mice preference towards male urine scent decayed over time when they were permitted to explore pheromones v/s neutral stimuli, water. On training them for the associations involving olfactory and whisker systems, it was established that they were able to memorize the location of opposite sex pheromones, when tested 15 days later. This memory was not formed either when the somatosensory inputs through whisker pad were blocked or when the pheromonal cues were replaced with that of same sex. The association between olfactory and somatosensory systems were further confirmed by the enhanced expression of the Activity regulated cytoskeleton protein. Further, the activation of main olfactory bulb circuitry by pheromone volatiles did not cause any modulation in learning and memorizing non-pheromonal volatiles. Our study thus provides the evidence for associations formed between different sensory modalities facilitating the long-term memory formation relevant to social and reproductive behaviors.
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neuroscience
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Discovery of dual inhibitors of KPC-3 and KPC-15 of Klebsiella pneumoniae :an in-silico molecular docking and dynamics study BackgroundThe development of carbapenem resistance against Klebsiella pneumoniae is a situation of grave concern and requires urgent attention. Among the KPC produced by K.pneumoniae, KPC-3, and KPC-15, play a significant role in the development of resistance to carbapenem.
Materials and methodsThe binding sites of KPC-3 and KPC-15 were predicted by the COACH server. Drug-like ligands from ZINC were then screened by ligand-based drug screening (LBVS) by keeping Relebactam as a template. The top 50,000 selected ligands were then screened by structure-based virtual screening using idock. For keeping an account of the dual inhibitors stability in complex with KPC-3 and KPC-15, MDS were carried out for each complex.
ResultsBased on consensus weighted ranks, the top 3 ligands with the dual inhibitory property are ZINC76060350 (consensus weighted rank - 1.5), ZINC05528590 (2), ZINC72290395 (3.5). All the top 3 dual inhibitors have a reasonable probability of passing through the blood-brain barrier. The RDKit and Morgan fingerprint scores between Relebactam and the top three ligands were 0.24, 0.22, 0.23, and 0.26, 0.19, 0.25, respectively (showing only 20% similarity). The MD simulation result revealed good binding stability of ligand ZINC05528590 with both KPC-3 and KPC-15, whereas ligand ZINC76060350 showed good binding stability to KPC-3.
ConclusionThe ligand ZINC05528590 could be taken forward to develop a new drug against a multi-resistant- Klebsiella pneumoniae infection. At the same time, ZINC76060350 can be considered to develop a new drug against KPC-15 resistant Klebsiella pneumoniae.
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bioinformatics
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SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the performance is highly dependent on protein and ligand features utilized for the DNN model. Moreover, in current models, the deciphering of how protein features determine the underlying principles that govern PLI is not trivial. In this work, we developed a DNN framework named SSnet that utilizes secondary structure information of proteins extracted as the curvature and torsion of the protein backbone to predict PLI. We demonstrate the performance of SSnet by comparing against a variety of currently popular machine and non-machine learning models using various metrics. We visualize the intermediate layers of SSnet to show a potential latent space for proteins, in particular to extract structural elements in a protein that the model finds influential for ligand binding, which is one of the key features of SSnet. We observed in our study that SSnet learns information about locations in a protein where a ligand can bind including binding sites, allosteric sites and cryptic sites, regardless of the conformation used. We further observed that SSnet is not biased to any specific molecular interaction and extracts the protein fold information critical for PLI prediction. Our work forms an important gateway to the general exploration of secondary structure based deep learning, which is not just confined to protein-ligand interactions, and as such will have a large impact on protein research while being readily accessible for de novo drug designers as a standalone package.
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bioinformatics
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Influence of native endophytic bacteria on the growth and bacterial crown rot tolerance of papaya (Carica papaya) The native plant microbiome is composed of diverse communities that influence its overall health, with some species known to promote plant growth and pathogen resistance. Here, we show the antimicrobial and growth promoting activities of autoclaved culture metabolites (ACMs) from native endophytic bacteria (NEB) in a papaya cultivar that is tolerant to bacterial crown rot (BCR) caused by Erwinia mallotivora. Initially, bacterial colonization in recovering tissues of this cultivar was observed before onset of tissue regeneration or regrowth. We further isolated and characterized these bacteria and were able to identify two culturable stem NEB under genera Kosakonia (EBW), related to Enterobacter, and Sphingomonas (EBY). We also identified root NEB (BN, BS and BT) under genus Bacillus. Inhibition assays indicated that ACMs from these NEB promptly (18-30h) and efficiently inhibited (60-65%) E. mallotivora proliferation in vitro. Interestingly, when ACMs from BN and EBW were inoculated in surface-sterilized papaya seeds, germination was variably retarded (20-60% reduction) depending on plant genotype, but plant biomass accumulation was significantly stimulated, at around two-fold increase. Moreover, greenhouse experiments show that ACMs from all isolates, especially EBW, significantly reduced BCR incidence and severity in susceptible genotype, at around two-fold. In general, our observations of pathogen antagonism, plant growth promotion leading to disease reduction by ACMs of native endophytic bacteria suggested its contribution to increased fitness of papaya and tolerance against the (re)emerging BCR disease.
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plant biology
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Adenosine receptor and its downstream targets, mod(mdg4) and Hsp70, work as a signaling pathway modulating cytotoxic damage in Drosophila Adenosine (Ado) is an important signaling molecule involved in stress responses. Studies in mammalian models have shown that Ado regulates signaling mechanisms involved in danger-sensing and tissue-protection. Yet, little is known about the role of Ado signaling in Drosophila. In the present study, we observed lower extracellular Ado concentration and suppressed expression of Ado transporters in flies expressing mutant huntingtin protein (mHTT). We altered Ado signaling using genetic tools and found that the overexpression of Ado metabolic enzymes, as well as the suppression of Ado receptor (AdoR) and transporters (ENTs), were able to minimize mHTT-induced mortality. We also identified the downstream targets of the AdoR pathway, the modifier of mdg4 (Mod(mdg4)) and heat-shock protein 70 (Hsp70), which carry out its function. Finally, we showed that a decrease in Ado signaling affect other Drosophila stress reactions, including paraquat and heat-shock treatments. Our study provides important insights into how Ado regulates stress responses in Drosophila.
|
genetics
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OBERON3 and SUPPRESSOR OF MAX2 1-LIKE proteins form a regulatory module specifying phloem identity Spatial specificity of cell fate decisions is central for organismal development. The phloem tissue mediates long-distance transport of energy metabolites along plant bodies and is characterized by an exceptional degree of cellular specialization. How a phloem-specific developmental program is implemented is, however, unknown. Here we reveal that the ubiquitously expressed PHD-finger protein OBE3 forms a central module with the phloem- specific SMXL5 protein for establishing phloem identity in Arabidopsis thaliana. By protein interaction studies and phloem-specific ATAC-seq analyses, we show that OBE3 and SMXL5 proteins form a complex in nuclei of phloem stem cells where they establish a phloem-specific chromatin profile. This profile allows expression of OPS, BRX, BAM3, and CVP2 genes acting as mediators of phloem differentiation. Our findings demonstrate that OBE3/SMXL5 protein complexes establish nuclear features essential for determining phloem cell fate and highlight how a combination of ubiquitous and local regulators generate specificity of developmental decisions in plants.
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plant biology
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Model balancing: in search of consistent metabolic states and in-vivo kinetic constants Enzyme kinetic constants in vivo are largely unknown, which limits the construction of large metabolic models. While model fitting, in principle, aims at fitting kinetic constants to measured metabolic fluxes, metabolite concentrations, and enzyme concentrations, the resulting estimation problems are typically non-convex and hard to solve, especially if models are large. Here we assume that metabolic fluxes are known and show how consistent kinetic constants, metabolite concentrations, and enzyme concentrations can be determined simultaneously from data. If one specific term is omitted - a term that penalises small enzyme concentrations - we obtain a convex optimality problem with a unique local optimum. The estimation method with or without this term, called model balancing, applies to models with a wide range of rate laws and accounts for thermodynamic constraints on kinetic constants and metabolite concentrations through thermodynamic forces. It can be used to estimate in-vivo kinetic constants from omics data, to complete and adjust available data, or to construct plausible metabolic states with a predefined flux distribution. As a demonstrative case, we balance a model of E. coli central metabolism with artificial or experimental data. The tests show what information about kinetic constants can be obtained from omics data, and reveal the practical limits of estimating in-vivo kinetic constants.
|
systems biology
|
Two distinct bacterial biofilm components trigger metamorphosis in the colonial hydrozoan Hydractinia echinata In the marine environment bacterial-induced metamorphosis of larvae is a widespread cross-kingdom communication phenomenon and critical for the persistence of many marine invertebrates. However, the identities of most inducing bacterial signals and the underlying cellular mechanisms remain enigmatic. Larvae of Hydractinia echinata provide an excellent model for investigating bacteria-stimulated settlement as they transform upon detection of the signal into the colonial adult stage within 24 h. Although H. echinata served as cell biological model system for decades, the influence of bacterial signals on the morphogenic transition remained largely unexplored. Using a bioassay-guided analysis, we first identified that specific bacterial (lyso)phospholipids, naturally present in bacterial biofilms, elicit metamorphosis in Hydractinia larvae in a dose-response matter. In particular, lysophospholipids as single compounds or in combinations at 50 {micro}M concentrations induced metamorphosis in up to 50% of all larvae phospholipid within 48 h. By using fluorescence-labeled bacterial phospholipids, we demonstrated their incorporation into the larval membranes, where interactions with internal signaling cascades could occur. In addition, two structurally distinct exopolysaccharides, the newly identified Rha-Man polysaccharide from Pseudoalteromonas sp. P1-9 and curdlan from Alcaligenes faecalis caused up to 75% of all larvae to transform within 24 h. We also found that combinations of (lyso)phospholipids and curdlan induced the transformation in almost all larvae within 24 h, thereby exceeding the morphogenic activity observed for single compounds and axenic bacterial biofilms. Our results demonstrate that multiple and structurally distinct bacterial-derived metabolites converge to induce high transformation rates of Hydractinia larvae, which might ensure optimal habitat selection despite the general widespread occurrence of both compound classes.
Significance StatementBacterial biofilms profoundly influence the recruitment and settlement of marine invertebrates, critical steps for diverse marine processes such as coral reef formation, marine fisheries and the fouling of submerged surfaces. Yet, the complex composition of biofilms often makes it challenging to characterize the individual signals and regulatory mechanisms. Developing tractable model systems to characterize these co-evolved interactions is the key to understand fundamental processes in evolutionary biology. Here, we characterized for the first time two types of bacterial signaling molecules that induce the morphogenic transition and analyzed their abundance and combinatorial activity. This study highlights the crucial role of the converging activity of multiple bacterial signals in development-related cross-kingdom signaling.
AreasMajor: Chemical Biology, Microbiology, Developmental Biology
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ecology
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Donut-like organization of inhibition underlies categorical neural responses in the midbrain Categorical neural responses underlie various forms of selection and decision-making. Such binary-like responses promote robust signaling of the winner in the presence of input ambiguity and neural noise. Here, we show that a donut-like inhibitory mechanism in which each competing option suppresses all options except itself, is highly effective at generating categorical neural responses. It surpasses motifs of feedback inhibition, recurrent excitation, and divisive normalization invoked frequently in decision-making models. We demonstrate experimentally not only that this mechanism operates in the midbrain spatial selection network in barn owls, but also that it is necessary for categorical signaling by it. The functional pattern of neural inhibition in the midbrain forms an exquisitely structured multi-holed donut consistent with this networks combinatorial inhibitory function for stimulus selection. Additionally, modeling reveals a generalizable neural implementation of the donut-like motif for categorical selection. Self-sparing inhibition may, therefore, be a powerful circuit module central to categorization.
|
neuroscience
|
Single cell transcriptome analysis reveals RGS1 as a new marker and promoting factor for T cell exhaustion in multiple cancers T cell exhaustion is one of the main reasons of tumor immune escape. Using single cell transcriptome data of CD8+ T cells in multiple cancers, we identified different cell types, in which Pre_exhaust and exhausted T cells participated in negative regulation of immune system process. By analyzing the co-expression network patterns and differentially expressed genes of Pre_exhaust, exhausted and effector T cells, we identified 35 genes related to T cell exhaustion, which high GSVA scores were associated with significantly poor prognosis in various cancers. In the differentially expressed genes, RGS1 showed the greatest fold change in Pre_exhaust and exhausted cells of three cancers compared with effector T cells, and high expression of RGS1 was also associated with poor prognosis in various cancers. Additionally, RGS1 protein was upregulated significantly in tumor tissues in the immunohistochemistry verification. Furthermore, RGS1 displayed positive correlation with the 35 genes, especially highly correlated with PDCD1, CTLA4, HAVCR2 and TNFRSF9 in CD8+ T cells and cancer tissues, indicating important roles of RGS1 in CD8+ T cell exhaustion. Considering the GTP-hydrolysis activity of RGS1 and significantly high mRNA and protein expression in cancer tissues, we speculated that RGS1 potentially mediate the T cell retention to lead to the persistent antigen stimulation, resulting in T cell exhaustion. In conclusion, our findings suggest that RGS1 is a new marker and promoting factor for CD8+ T cell exhaustion, and provide theoretical basis for research and immunotherapy of exhausted cells.
|
cancer biology
|
The making of calibration sausage exemplified by recalibrating the transcriptomic timetree of jawed vertebrates Molecular divergence dating has the potential to overcome the incompleteness of the fossil record in inferring when cladogenetic events (splits, divergences) happened, but needs to be calibrated by the fossil record. Ideally but unrealistically, this would require practitioners to be specialists in molecular evolution, in the phylogeny and the fossil record of all sampled taxa, and in the chronostratigraphy of the sites the fossils were found in. Paleontologists have therefore tried to help by publishing compendia of recommended calibrations, and molecular biologists unfamiliar with the fossil record have made heavy use of such works (in addition to using scattered primary sources and copying from each other). Using a recent example of a large node-dated timetree inferred from molecular data, I reevaluate all thirty calibrations in detail, present the current state of knowledge on them with its various uncertainties, rerun the dating analysis, and conclude that calibration dates cannot be taken from published compendia or other secondary or tertiary sources without risking strong distortions to the results, because all such sources become outdated faster than they are published: 50 of the sources I cite to constrain calibrations were published in 2019, half of the total of 276 after mid-2016, and 90% after mid-2005. It follows that the present work cannot serve as such a compendium either; in the slightly longer term, it can only highlight known and overlooked problems. Future authors will need to solve each of these problems anew through a thorough search of the primary paleobiological and chronostratigraphic literature on each calibration date every time they infer a new timetree; and that literature is not optimized for that task, but largely has other objectives.
|
evolutionary biology
|
Optimal evolutionary control for artificial selection on molecular phenotypes Controlling an evolving population is an important task in modern molecular genetics, including directed evolution for improving the activity of molecules and enzymes, in breeding experiments in animals and in plants, and in devising public health strategies to suppress evolving pathogens. An optimal intervention to direct evolution should be designed by considering its impact over an entire stochastic evolutionary trajectory that follows. As a result, a seemingly suboptimal intervention at a given time can be globally optimal as it can open opportunities for desirable actions in the future. Here, we propose a feedback control formalism to devise globally optimal artificial selection protocol to direct the evolution of molecular phenotypes. We show that artificial selection should be designed to counter evolutionary tradeoffs among multi-variate phenotypes to avoid undesirable outcomes in one phenotype by imposing selection on another. Control by artificial selection is challenged by our ability to predict molecular evolution. We develop an information theoretical framework and show that molecular time-scales for evolution under natural selection can inform how to monitor a population in order to acquire sufficient predictive information for an effective intervention with artificial selection. Our formalism opens a new avenue for devising artificial selection methods for directed evolution of molecular functions.
|
evolutionary biology
|
Evidence for novel transient cell clusters in the neonatal mouse retina Waves of spontaneous activity sweep across the neonatal mouse retinal ganglion cell (RGC) layer, driven by directly interconnected cholinergic starburst amacrine cells from postnatal day (P) 0-10, followed by waves driven by glutamatergic bipolar cells. We found transient clusters of auto-fluorescent cells in the RGC layer during the period of cholinergic waves. They appear around the optic nerve head at P2 and become gradually displaced towards the periphery between P2-8 and then they disappear. Pan-retinal multielectrode array recordings reveal that cholinergic wave origins follow a similar, non-random developmental center-to-periphery pattern. Electrical imaging unmasks hotspots of dipole electrical activity occurring in the vicinity of wave origins. We propose that these activity hotspots are the sites for wave initiation and may originate from the transient cell clusters, reminiscent of activity in transient subplate neurons in the developing cortex, suggesting a universal hyper-excitability mechanism in developing CNS networks during the critical period for brain wiring.
|
neuroscience
|
Evolution of olfactory receptors tuned to mustard oils in herbivorous Drosophilidae The diversity of herbivorous insects is attributed to their propensity to specialize on toxic plants. In an evolutionary twist, toxins betray the identity of their bearers when herbivores co-opt them as cues for host-plant finding, but the mechanisms underlying this process are poorly understood. We focused on Scaptomyza flava, an herbivorous drosophilid specialized on isothiocyanate (ITC)-producing (Brassicaceae) plants, and identified Or67b paralogs that were triplicated as mustard-specific herbivory evolved. Using heterologous systems for the expression of olfactory receptors, we found that S. flava Or67bs, but not homologs from microbe-feeding relatives, responded selectively to ITCs, each paralog detecting different ITC subsets. Consistent with this, S. flava was attracted to ITCs, as was Drosophila melanogaster expressing S. flava Or67b3 in the homologous Or67b olfactory circuit. Thus, our results show that plant toxins were likely co-opted as olfactory attractants through gene duplication and functional specialization (neofunctionalization and subfunctionalization) in drosophilid flies.
|
evolutionary biology
|
Organelle specific protein profiling with light mediated proximal labeling in living cells Organelle specific protein identification is essential for understanding how cell functions on a subcellular level. Here, we report a light mediated proximal labeling (LIMPLA) strategy for organelle specific protein profiling in living cells. In this strategy, various commercial mitochondria-localized fluorescent trackers, such as Mitoview 405 and Rhodamine 123, can activate 2-Propynylamine (PA) to label proximal proteins in mitochondria under illumination. PA tagged proteins are subsequently derivatized via click chemistry with azido fluorescent dye for imaging or with azido biotin for further enrichment and mass-spec identification. This strategy can be generalized to other organelles specific protein labeling. For example, proteins in nucleus are labeled by utilizing the commercial nucleus tracker DRAQ5. As compared with other chemical strategies for subcellular protein labeling, there are several advantages for this LIMPLA strategy. First, this approach allows minimal interference to the cells status by avoiding exogenous gene tansduction and some special treatment such as hydrogen peroxide or serum starvation. Second, all reagents used in this strategy are commercially available without additional synthesis work. Further, this strategy holds the potential for analyzing proximal proteins of specific macromolecules that can be tagged with fluorescent dye by metabolic labeling strategy.
|
biochemistry
|
NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep-learning method NanoCaller, which detects SNPs using long-range haplotype information, then phases long reads with called SNPs and calls indels with local realignment. Evaluation on 8 human genomes demonstrated that NanoCaller generally achieves better performance than competing approaches. We experimentally validated 41 novel variants in a widely-used benchmarking genome, which cannot be reliably detected previously. In summary, NanoCaller facilitates the discovery of novel variants in complex genomic regions from long- read sequencing.
|
bioinformatics
|
Graded recruitment of pupil-linked neuromodulation by parametric stimulation of the vagus nerve AO_SCPLOWBSTRACTC_SCPLOWVagus nerve stimulation (VNS) is thought to affect neural activity by recruiting brain-wide release of neuromodulators. VNS is used in treatment-resistant epilepsy, and is increasingly being explored for other disorders, such as depression, and as a cognitive enhancer. However, the promise of VNS is only partially fulfilled due to a lack of mechanistic understanding of the transfer function between stimulation parameters and neuromodulatory response, together with a lack of biosensors for assaying stimulation efficacy in real time. We here develop an approach to VNS in head-fixed mice on a treadmill and show that pupil dilation is a reliable and convenient biosensor for VNS-evoked cortical neuromodulation. In an optimal zone of stimulation parameters, current leakage and off-target effects are minimized and the extent of pupil dilation tracks VNS-evoked basal-forebrain cholinergic axon activity in neocortex. Thus, pupil dilation is a sensitive readout of the moment-by-moment, titratable effects of VNS on brain state.
|
neuroscience
|
Tracking niche change through time: simultaneous inference of ecological niche evolution and estimation of contemporary niches O_LIThe ecological niche of species is often studied from two different perspectives. Environmental niche modelling (ENM) infers a species current niche from contemporary occurrence records, while phylogenetic comparative methods (PCM) infer the history of niche evolution. Although these two areas of research are conceptually linked, they are analysed independently, within separate analytical frameworks.
C_LIO_LIHere we provide a new method, NEMo (Niche Evolution Model), for simultaneous inference of niche evolution and estimation of contemporary niches of species. NEMo explicitly models three fundamental processes of niche evolution - adaptation, speciation, and dispersal - applying a reversible jump algorithm to infer occurrences of these processes on a phylogeny. The model permits ENMs to account for the role of history in shaping current species distributions, and offers more realistic models of evolution in PCMs.
C_LIO_LISimulations show that NEMo has high accuracy for estimating the ecological niche of species, and reasonable power to identify the occurrences of the three processes on phylogeny. When applied to a real case study (the Australian plant genus Acacia), the method is more effective at predicting a key environmental niche axis (salt tolerance) than using ENM alone, and it infers temporal patterns in the evolution of drought tolerance in response to aridification that are consistent with prior expectations
C_LIO_LINEMo makes it possible to combine many types of data to study niche evolution and estimate species niches, not only species distributions and phylogeny, but also paleoclimate, species tolerance range, and fossil records.
C_LI
|
evolutionary biology
|
Predictive olfactory learning in Drosophila Olfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.
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neuroscience
|
The co-stimulatory activity of Tim-3 requires Akt and MAPK signaling and immune synapse recruitment Expression of the transmembrane protein Tim-3 is increased on dysregulated T cells undergoing chronic T cell activation, including in chronic infection and solid tumors. We and others previously reported that Tim-3 exerts apparently paradoxical co-stimulatory activity in T cells (and other cells), including enhancement of ribosomal S6 protein phosphorylation (pS6). Here we examined the upstream signaling pathways that control Tim3-mediated increases in pS6 in T cells. We have also defined the localization of Tim-3 relative to the T cell immune synapse and impacts on downstream signaling. Recruitment of Tim-3 to the immune synapse was mediated exclusively by the transmembrane domain, replacement of which impaired Tim-3 co-stimulation of pS6. Strikingly, enforced localization of the Tim-3 cytoplasmic domain to the immune synapse in the context of a chimeric antigen receptor still allowed for robust T cell activation. Our findings are consistent with a model whereby Tim-3 enhances TCR-proximal signaling under acute conditions.
One Sentence SummaryHere we define elements of signaling and localization associated with Tim-3 co-stimulatory function in T cells.
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immunology
|
A standardized gnotobiotic mouse model harboring a minimal 15-member mouse gut microbiota recapitulates SOPF/SPF phenotypes Mus musculus is the classic mammalian model for biomedical research. Despite global efforts to standardize breeding and experimental procedures, the undefined composition and interindividual diversity of the microbiota of laboratory mice remains a limitation. In an attempt to standardize the gut microbiome in preclinical mouse studies, we developed a simplified mouse microbiota composed of 15 strains from 7 of the 20 most prevalent bacterial families representative of the fecal microbiota of C57BL/6J Specific (and Opportunistic) Pathogen-Free (SPF/SOPF) animals and derived a new standardized gnotobiotic mouse model called GM15. GM15 recapitulates extensively the functionalities found in the C57BL/6J SOPF microbiota metagenome, and GM15 animals are phenotypically similar to SOPF or SPF animals in two different facilities. They are also less sensitive to the deleterious effects of post-weaning malnutrition. The GM15 model provides increased reproducibility and robustness of preclinical studies by limiting the confounding effect of fluctuation in microbiota composition, and offers new opportunities for research focused on how the microbiota shapes host physiology in health and disease.
|
microbiology
|
Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP) Ancestral sequence reconstruction is a technique that is gaining widespread use in molecular evolution studies and protein engineering. Accurate reconstruction requires the ability to handle appropriately large numbers of sequences, as well as insertion and deletion ("indel") events, but available approaches exhibit limitations. To address these limitations, we developed Graphical Representation of Ancestral Sequence Predictions (GRASP), which efficiently implements maximum likelihood methods to enable the inference of ancestors of families with more than 10,000 members. GRASP implements partial order graphs (POGs) to represent and infer insertion and deletion events across ancestors, enabling the identification of building blocks for protein engineering.
To validate the capacity to engineer novel proteins from realistic data, we predicted ancestor sequences across three distinct enzyme families: glucose-methanol-choline (GMC) oxidoreductases, cytochromes P450, and dihydroxy/sugar acid dehydratases (DHAD). All tested ancestors demonstrated enzymatic activity. Our study demonstrates the ability of GRASP (1) to support large data sets over 10,000 sequences and (2) to employ insertions and deletions to identify building blocks for engineering biologically active ancestors, by exploring variation over evolutionary time.
Author summaryMassive sequencing projects expose the extent of natural, genetic diversity. Here, we describe a method with capacity to perform ancestor sequence reconstruction from data sets in excess of 10,000 sequences, poised to recover ancestral diversity, including the evolutionary events that determine present-time biological function and structure.
We introduce a novel strategy for suggesting "indel variants" that are distinct from, but can be explored alongside, substitution variants for creating ancestral libraries. We demonstrate how indels can be used as building blocks to form "hybrid ancestors"; based on this strategy, we synthesise ancestor variants, with varying enzymatic activities, for wide-ranging applications in the biotechnology sector.
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bioinformatics
|
Designing signaling environments to steer transcriptional diversity in neural progenitor cell populations Stem and progenitor populations within developing embryos are diverse, composed of different subpopulations of precursor cells with varying developmental potential. How these different subpopulations are coordinately regulated by their signaling environments is not well understood. In this paper we develop a framework for controlling progenitor population structure in cell culture using high-throughput single cell mRNA-seq and computational analysis. We find that the natural transcriptional diversity of neural stem cell populations from the developing mouse brain collapses during in vitro culture. Cell populations are depleted of committed neuroblast progenitors and become dominated by a single pre-astrocytic cell population. By analyzing the response of neural stem cell populations to forty combinatorial signaling conditions, we demonstrate that signaling environments can restructure cell populations by modulating the relative abundance of pre-astrocytic and pre-neuronal subpopulations according to a simple log-linear model. Our work demonstrates that single-cell RNA-seq can be applied to learn how to modulate the diversity of stem cell populations, providing a new strategy for population-level stem cell control.
HighlightsO_LINatural progenitor diversity in the brain collapses during in vitro culture to a single progenitor type
C_LIO_LILoss of progenitor diversity alters fate potential of cells during differentiation
C_LIO_LILarge scale single-cell signaling screen identifies signals that reshape population structure towards neuronal cell types
C_LIO_LISignals regulate population structure according to a simple log-linear model
C_LI
GRAPHICAL ABSTRACT
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/890087v3_ufig1.gif" ALT="Figure 1">
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[email protected]@c0e69borg.highwire.dtl.DTLVardef@640b20org.highwire.dtl.DTLVardef@16779e_HPS_FORMAT_FIGEXP M_FIG C_FIG
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systems biology
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Effect of high-frequency low-intensity pulsed electric field on protecting SH-SY5Y cells against hydrogen peroxide and β-amyloid-induced cell injury via ERK pathway As the most common type of neurodegenerative diseases (NDDs), Alzheimers disease (AD) is thought to be caused mainly by the excessive aggregation of {beta}-amyloid protein (A{beta}). However, a growing number of studies have found that reactive oxygen species (ROS) play a key role in the onset and progression of AD. The present study aimed to probe the neuroprotective effect of high-frequency low-intensity pulsed electric field (H-LIPEF) for SH-SY5Y cells against hydrogen peroxide (H2O2) and A{beta}-induced cytotoxicity. By looking in a systematic way into the frequency- and amplitude-dependent neuroprotective effect of pulsed electric field (PEF), the study finds that H-LIPEF at 200 Hz produces the optimal protective effect for SH-SY5Y cells. The underlying mechanisms were confirmed to be due to the activation of extracellular signal-regulated kinase (ERK) pathway and the downstream prosurvival and antioxidant proteins. Because the electric field can be modified to focus on specific area in a non-contact manner, the study suggests that H-LIPEF holds great potential for treating NDDs, whose effect can be further augmented with the administering of drugs or natural compounds at the same time.
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neuroscience
|
Binary and analog variation of synapses between cortical pyramidal neurons Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (L2/3 pyramidal cells), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects. We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes (Arellano et al. 2007) by a log-normal distribution (Loewenstein, Kuras, and Rumpel 2011; de Vivo et al. 2017; Santuy et al. 2018). A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well-modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size (Sorra and Harris 1993; Koester and Johnston 2005; Bartol et al. 2015; Kasthuri et al. 2015; Dvorkin and Ziv 2016; Bloss et al. 2018; Motta et al. 2019). We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences. We discuss the implications for the stability-plasticity dilemma.
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neuroscience
|
Material category of visual objects computed from specular image structure Recognising materials and their properties from visual information is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to the physical properties that define materials. While studies have investigated how material properties like surface gloss are perceived from regularities in image structure, such as the size, sharpness, contrast, and position of bright patches caused by specular reflections, little is known how this translates to the recognition of different material classes like plastic, pearl, satin, or steel, and the underlying mechanisms involved. We investigated this by collecting human psychophysical judgments about complex glossy objects rendered in natural illumination fields. We found that variations in specular image structure - produced either by different reflectance properties or direct manipulation of image features - caused categorical shifts in material appearance, suggesting that specular reflections provide diagnostic information about a wide range of material classes, including many that should be defined by more complex scattering functions. Moreover, differences in material category were predicted by, but also appeared to mediate, cues for surface gloss, providing evidence against a traditional feedforward view of neural processing that assumes combinations of mid-level properties mediate our holistic, categorical impressions. Instead, our results suggest that the image structure that triggers our perception of surface gloss plays a direct role in visual categorisation and, importantly, that the perception and neural processing of stimulus properties should not be studied in isolation but rather in the context of recognition.
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neuroscience
|
An antigenic diversification threshold for falciparum malaria transmission at high endemicity In malaria and several other important infectious diseases, high prevalence occurs concomitantly with incomplete immunity. This apparent paradox poses major challenges to malaria elimination in highly endemic regions, where asymptomatic Plasmodium falciparum infections are present across all age classes creating a large reservoir that maintains transmission. This reservoir is in turn enabled by extreme antigenic diversity of the parasite and turnover of new variants. We present here the concept of a threshold in local pathogen diversification that defines a sharp transition in transmission intensity below which new antigen-encoding genes generated by either recombination or migration cannot establish. Transmission still occurs below this threshold, but diversity of these genes can neither accumulate nor recover from interventions that further reduce it. An analytical expectation for this threshold is derived and compared to numerical results from a stochastic individual-based model of malaria transmission that incorporates the major antigen-encoding multigene family known as var. This threshold corresponds to an "innovation" number we call Rdiv; it is different from, and complementary to, the one defined by the classic basic reproductive number of infectious diseases, R0, which does not easily apply under large and dynamic strain diversity. This new threshold concept can be exploited for effective malaria control and applied more broadly to other pathogens with large multilocus antigenic diversity.
Author summaryThe vast diversity of the falciparum malaria parasite as seen by the immune system of hosts in high transmission regions, underlies both high prevalence of asymptomatic infections and partial protection to re-infection despite previous exposure. This large antigenic diversity of the parasite challenges control and elimination efforts. We propose a threshold quantity for antigenic innovation, we call Rdiv, measuring the potential of transmission to accumulate new antigenic variants over time. When Rdiv is pushed below one by reduced transmission intensity, new genes encoding this variation can no longer accumulate, resulting in a lower number of strains and facilitating further intervention. This innovation number can be applied to other infectious diseases with fast turnover of antigens, where large standing diversity similarly opposes successful intervention.
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evolutionary biology
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Epitope-tagging of the endogenous murine BiP/GRP78/Hspa5 locus allows direct analysis of the BiP interactome and protein misfolding in vivo. BiP/GRP78, encoded by the Hspa5 gene, is the major HSP70 family member in the endoplasmic reticulum (ER) lumen, and controls ER protein folding. The essential functions of BiP in facilitating proper protein folding are mainly mediated through its dynamic interaction with unfolded or misfolded client proteins, and by serving as a negative regulator of the Unfolded Protein Response. A mechanistic understanding of the dynamics of BiP interaction with its protein partners is essential to understand ER biology, and therefore, we have sought to develop a tractable model to study misfolded protein interaction with BiP. For this purpose, we have used homologous recombination to insert a 3xFLAG epitope tag into the endogenous murine Hspa5 gene, just upstream from the essential KDEL signal necessary for ER localization of BiP. Tagging BiP in this way did not alter Hspa5 expression under basal or ER-stress induced conditions in hepatocytes ex vivo or in fibroblasts. Furthermore, the tag did not alter the cellular localization of BiP or its functionality. All of these findings in primary tissue culture were also confirmed in vivo in livers of heterozygous mice harboring one WT and one FLAG-tagged Hspa5 allele. Hepatocyte-specific BiP-FLAG modification did not alter liver function or UPR signaling. Importantly, immunoprecipitation with anti-FLAG antibody completely pulled down FLAG-tagged BiP from lysates of BiP-FLAG expressing livers. Affinity purification-mass spectrometry (AP-MS) of BiP-FLAG protein complexes isolated from the BiP-FLAG-expressing livers of tunicamycin (TM)- and vehicle-treated mice revealed a marked increase in interaction of glycoproteins with BiP-FLAG in response to inhibition of N-glycosylation due to TM-treatment, validating utility of our BiP-Flag mice as a tool to identify ER misfolded proteins in vivo. Significantly, our AP-MS analysis also provided in vivo evidence demonstrating that BiP-FLAG binds to UPR transducers IRE1 and PERK under basal conditions but is released upon TM-treatment to activate UPR. We have also employed this mouse model to demonstrate that proinsulin in pancreatic {beta} cells misfolds and interacts with BiP-FLAG in healthy mice. In summary, we generated a novel model that can be used to investigate the BiP interactome in vivo under physiological and pathophysiological conditions in a cell type-specific manner. This tool provides, for the first time, an unbiased approach to identify unfolded and misfolded BiP-client proteins, and a new approach to study ER protein misfolding in a cell-type and temporal manner to uncover the role of BiP in many essential ER processes.
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molecular biology
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Plant Trans-Golgi Network/Early Endosome pH regulation requires Cation Chloride Cotransporter (CCC1) Plant cells maintain a low luminal pH in the Trans-Golgi-Network/Early Endosome (TGN/EE), the organelle in which the secretory and endocytic pathways intersect. Impaired TGN/EE pH regulation translates into severe plant growth defects. The identity of the proton pump and proton/ion antiporters that regulate TGN/EE pH have been determined, but an essential component required to complete the TGN/EE membrane transport circuit remains unidentified - a pathway for cation and anion efflux. Here, we have used complementation, genetically encoded fluorescent sensors, and pharmacological treatments to demonstrate that the TGN/EE localised Arabidopsis Cation Chloride Cotransporter (CCC1) is this missing component necessary for regulating TGN/EE pH and function. Loss of CCC1 function leads to alterations in TGN/EE-mediated processes including endo- and exocytosis, and trafficking to the vacuole, and response to abiotic stress, consistent with the multitude of phenotypes observed in ccc1 knockout plants. This discovery places CCC1 as a central component of plant cellular function.
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plant biology
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To Group or not to group: Group size dynamics and intestinal parasites in Indian peafowl populations Animals can form groups for various reasons including safety from predators, access to potential mates and benefits of allo-parental care. However, there are costs associated with living in a group such as competition for food and/or mates with other members of the group, higher chances of disease transmission, etc. Group size dynamics can change with the biotic and abiotic environment around individuals. In the current study, we explored the links between group size dynamics and intestinal parasites of Indian peafowl (Pavo cristatus) in the context of seasons and food provisioning. Data for group size was collected across three seasons (Pre-Monsoon, Monsoon and Post-Monsoon) at three field sites (Morachi Chincholi, Nashik and Rajasthan). Individual and group sightings of peafowl were noted down along with group size and composition (no. of males, females, adults, juveniles, sub-adults). Faecal samples were collected from food provision and non-provision areas across the same three seasons at same field sites. Parasite load in the samples was quantified using microscopic examination. Group size was significantly higher in Pre-Monsoon season as compared to Monsoon and Post-Monsoon seasons. Monsoon and Post-Monsoon seasons had higher intestinal parasite prevalence and load as compared to Pre-Monsoon season. Thus, group size and intestinal parasites of Indian peafowl have an inverse relationship across seasons. Parasite load was significantly greater at food provision sites as compared to non-provision sites while parasite prevalence was comparable. Aggregation of individuals at the food provision sites may influence the parasite transmission and group-size dynamics in Indian peafowl. In conclusion, Indian peafowl are behaviourally plastic and fission-fusion of social groups may allow them to tackle ecological pressures such as predation and parasite transmission in different seasons.
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ecology
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Consequences of combining sex-specific life-history traits Males and females evolved distinct life-history strategies, reflected in diverse inter-linked life-history traits. The sex that allocates more resources towards offspring relies on an increased life span, and long life requires an efficient immune system. The other sex needs to attract mates and thus allocates its resources towards ornamentation, which may negatively correlate with investment into the immune defense. Such sex-specific resource allocation trade-offs are not always strictly female or male-specific but may depend on the overall resources allocated towards life-history traits. Informed by experimental data, we designed a theoretical framework that combines multiple life-history traits. We disentangled specific life-history strategies from particular sex, allowing us to include species with reversed sex-roles and male parental investment. We computed the lifetime reproductive success (combining fitness components from diverse sex-specific life-history traits) observing a strong bias in adult sex ratio depending on sex-specific resource allocation towards life-history traits. Overall, our work provides a generalized method to combine various life-history traits with sex-specific differences to calculate lifetime reproductive success. The results explain specific population-level empirical observations as a consequence of sexual dimorphism in life-history traits.
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evolutionary biology
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