title: Quinacrine binds to the kinase domain of FGFR1 and inhibits its activity

abstract:
BackgroundFGF family receptors, especially FGFR1, have been widely implicated for their potential role in the promotion of oncogenesis and chemoresistance in lung cancer. Quinacrine, an anti-malarial drug, has been widely reported to exhibit anti-neoplastic properties through the activation of p53 and simultaneous inhibition of NF-kB signaling pathways in cancer cells.

MethodsThe binding of QC to FGFR1 was studied using molecular docking and molecular dynamics simulation studies. The experimental kinase activity assay for the protein was performed using a luminescence-based kinase assay. FGF-induced phosphorylation and proliferation were studied by cell counting and western blotting. Matrigel-based cell migration was conducted to assess migration activity.

ResultsQC interacted with multiple residues around the kinase insert domain of FGFR1 through hydrogen bonding, hydrophobic interactions, and water bridges. The kinase activity inhibition assay demonstrated a significant reduction in FGFR1 kinase activity by QC at higher concentrations, which was further observed at the cellular level in inhibition of FGFR1 phosphorylation and proliferation by QC at higher exposure concentrations of FGF stimulated cells. These effects were further validated downstream in the FGF-induced activation of cell migration.

ConclusionQC did form a stable interaction with residues of FGFR1 at another allosteric site surrounding the kinase domain, leading to inhibition of its kinase activity at higher drug concentrations. This effect was further observed at the cellular level in both acidic and basic FGF ligand-induced proliferation, phosphorylation of FGFR1, and cell migration, where a trend of significant reduction in activity was observed at higher drug concentrations.


title: Detection of allele-specific expression in spatial transcriptomics with spASE

abstract: Allele-specific expression (ASE), or the preferential expression of one allele, can be observed in transcriptomics data from early development throughout the lifespan. However, the prevalence of spatial and cell type-specific ASE variation remains unclear. Spatial transcriptomics technologies permit the study of spatial ASE patterns genome-wide at near-single-cell resolution. However, the data are highly sparse, and confounding between cell type and spatial location present further statistical challenges. Here, we introduce spASE (https://github.com/lulizou/spase), a computational framework for detecting spatial patterns in ASE within and across cell types from spatial transcriptomics data. To tackle the challenge presented by the low signal to noise ratio due to the sparsity of the data, we implement a spatial smoothing approach that greatly improves statistical power. We generated Slide-seqV2 data from the mouse hippocampus and detected ASE in X-chromosome genes, both within and across cell type, validating our ability to recover known ASE patterns. We demonstrate that our method can also identify cell type-specific effects, which we find can explain the majority of the spatial signal for autosomal genes. The findings facilitated by our method provide new insight into the uncharacterized landscape of spatial and cell type-specific ASE in the mouse hippocampus.

category: genomics


title: A 3'-end capture sequencing method for high-throughput targeted gene expression profiling

abstract: Molecular phenotyping through shallow 3-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3-end library preparation with 3-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3-end RNA-sequencing, 3-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.


title: Genetic architecture of dispersal and local adaptation drives accelerating range expansions

abstract: Contemporary evolution has the potential to significantly alter biotic responses to global change, including range expansion dynamics and biological invasions. However, predictive models often make highly simplifying assumptions about the genetic architecture underlying relevant traits. This can be problematic since genetic architecture defines evolvability, that is, evolutionary rates, and higher order evolutionary processes, which determine whether evolution will be able to keep up with environmental change or not. Therefore, we here study the impact of the genetic architecture of dispersal and local adaptation, two central traits of high relevance for range expansion dynamics, on the speed and variability of range expansions into an environmental gradient, such as temperature. In our theoretical model we assume that dispersal and local adaptation traits result from the products of two non-interacting gene-regulatory networks (GRNs). We compare our model to simpler quantitative genetics models and show that in the GRN model, range expansions are accelerated, faster and more variable. Increased variability implies that these evolutionary changes reduce predictability. We further find that acceleration in the GRN model is primarily driven by an increase in the rate of local adaptation to novel habitats which results from greater sensitivity to mutation (decreased robustness) and increased gene expression. Our results highlight how processes at microscopic scales, here, within genomes, can impact the predictions of large scale, macroscopic phenomena, such as range expansions, by modulating the rate of evolution.

category: evolutionary biology


title: cacna2d3, a voltage-gated calcium channel subunit, functions in vertebrate habituation learning and the startle sensitivity threshold

abstract: The ability to filter sensory information into relevant versus irrelevant stimuli is a fundamental, conserved property of the central nervous system and is accomplished in part through habituation learning. Synaptic plasticity that underlies habituation learning has been described at the cellular level, yet the genetic regulators of this plasticity remain poorly understood, as do circuits that mediate sensory filtering. A forward genetic screen for zebrafish genes that control habituation learning identified a mutant allele doryp177 that caused reduced habituation of the acoustic startle response. Whole-genome sequencing identified the calcium voltage-gated channel auxiliary subunit alpha-2/delta-3 (cacna2d3) as a candidate gene affected in doryp177 mutants. Behavioral characterization of larvae homozygous for two additional, independently derived mutant alleles of cacna2d3, together with failure of these alleles to complement doryp177, confirmed a critical role for cacna2d3 in habituation learning. Notably, detailed analyses of the acoustic response in mutant larvae also revealed increased startle sensitivity to acoustic stimuli, suggesting a broader role for cacna2d3 in controlling innate response thresholds to acoustic stimuli. Taken together, our data demonstrate a critical role for cacna2d3 in sensory filtering, a process that is disrupted in human CNS disorders, e.g. ADHD, schizophrenia, and autism.

category: neuroscience


title: Predicting the functional effects of voltage-gated potassium channel missense variants with multi-task learning

abstract:
PurposeVariants in genes encoding voltage-gated potassium channels are associated with a broad spectrum of neurological diseases including epilepsy, ataxia, and intellectual disability. Knowledge of the resulting functional changes, characterized as overall ion channel gain- or loss-of-function, is essential to guide clinical management including precision medicine therapies. However, for an increasing number of variants, little to no experimental data is available. New tools are needed to evaluate variant functional effects.

MethodsWe catalogued a comprehensive dataset of 959 functional experiments across 19 voltage-gated potassium channels, leveraging data from 782 unique disease-associated and synthetic variants. We used these data to train a taxonomy-based multi-task learning support vector machine (MTL-SVM), and compared performance to a baseline of standard SVMs.

ResultsMTL-SVM maintains channel family structure during model training, improving overall predictive performance (mean balanced accuracy 0.729 {+/-} 0.029, AU-ROC 0.757 {+/-} 0.039) over baseline (mean balanced accuracy 0.645 {+/-} 0.041, AU-ROC 0.710 {+/-} 0.074). We can obtain meaningful predictions even for channels with few known variants (KCNC1, KCNQ5).

ConclusionOur model enables functional variant prediction for voltage-gated potassium channels. It may assist in tailoring current and future precision therapies for the increasing number of patients with ion channel disorders.

category: bioinformatics


title: Information flow across the cortical timescales hierarchy during narrative comprehension

abstract: When listening to spoken narratives, we must integrate information over multiple, concurrent timescales, building up from words to phrases to sentences to a coherent narrative. Recent evidence suggests that the brain relies on a chain of hierarchically organized areas with increasing temporal receptive windows to process naturalistic narratives. In this study, we use inter-subject functional connectivity to reveal a stimulus-driven information flow along the cortical hierarchy. Using cross-correlation analysis to estimate the time lags between six functional networks, we found a fixed temporal sequence of information flow, starting in early auditory areas, followed language areas, the attention network, and lastly the default mode network. This gradient is consistent across eight distinct stories but absent in resting-state and scrambled story data, indicating that the lag gradient reflects the construction of narrative features. Finally, we simulate a variety of narrative integration models and demonstrate that nested narrative structure along with the gradual accumulation of information within the boundaries of linguistic events at each level of the processing hierarchy is sufficient to reproduce the lag gradient. Taken together, this study provides a computational framework for how information flows along the cortical hierarchy during narrative comprehension.


title: The functional evolution of termite gut microbiota

abstract: Termites primarily feed on lignocellulose or soil in association with specific gut microbes. The functioning of the termite gut microbiota is partly understood in a handful of wood-feeding pest species, but remains largely unknown in other taxa. We intend to feel this gap and provide a global understanding of the functional evolution of termite gut microbiota. We sequenced the gut metagenomes of 145 samples representative of the termite diversity. We show that the prokaryotic fraction of the gut microbiota of all termites possesses similar genes for carbohydrate and nitrogen metabolisms, in proportions varying with termite phylogenetic position and diet. The presence of a conserved set of gut prokaryotic genes implies that key nutritional functions were present in the ancestor of modern termites. Furthermore, the abundance of these genes largely correlated with the host phylogeny. Finally, we found that the adaptation to a diet of soil by some termite lineages was accompanied by a change in the stoichiometry of genes involved in important nutritional functions rather than by the acquisition of new genes and pathways. Our results reveal that the composition and function of termite gut prokaryotic communities have been remarkably conserved since termites first appeared [~]150 million years ago. Therefore, the "world smallest bioreactor" has been operating as a multipartite symbiosis composed of termites, archaea, bacteria, and cellulolytic flagellates since its inception.


title: Fitness and mating consequences of variation in male allocation in a wind pollinated plant

abstract: In hermaphrodites, the allocation of resources to each sex function can influence fitness through reproductive success and mating success. In wind pollinated plants, sex allocation theory predicts that male fitness increases linearly with investment of resources into male function. However, there have been few empirical tests of this prediction. We experimentally manipulated allocation to male function in Ambrosia artemisiifolia (common ragweed) in a field experiment and measured mating success using genetic assays. We investigated the effects of various morphological traits and flowering phenology on male fitness, and on male and female mate diversity. Our results provide evidence for a linear relation between allocation to male function and fitness. We find earlier onset of male flowering time increases reproductive success, while later onset flowering time increases the probability of mating with diverse individuals. This research is among the first empirical studies testing the prediction of linear male fitness returns in wind pollinated plants. Our results provide insight into the large investment into male function by wind pollinated plants and temporal variation in sex allocation.


title: Rapid genomic evolution in Brassica rapa with bumblebee selection in experimental evolution

abstract: Insect pollinators shape rapid phenotypic evolution of traits related to floral attractiveness and plant reproductive success. However, the underlying genomic changes and their impact on standing genetic variation remain largely unknown despite their importance in predicting adaptive responses in nature or in crops artificial selection. Here, based on a previous, nine generation experimental evolution study with fast cycling Brassica rapa plants adapting to bumblebees, we document genomic evolution associated to the adaptive process. We performed a genomic scan of the allele frequency changes along the genome and estimated the nucleotide diversity and genomic variance changes. We detected signature of selection associated with rapid changes in allelic frequencies on multiple loci. During experimental evolution, we detected an increase in overall genomic variance, whereas for loci under selection, a reduced variance was apparent in both replicates suggesting a parallel evolution. Our study highlights the polygenic nature of short-term pollinator adaptation and the importance of a such genetic architecture in the maintenance of genomic variance during strong natural selection by biotic factors.


title: The Evolutionary Dynamics of Hyperparasites

abstract: Evolutionary theory has typically focused on pairwise interactions, such as those between hosts and parasites, with relatively little work on more complex interactions including hyperparasites: parasites of parasites. Hyperparasites are common in nature, with the chestnut blight fungus virus CHV-1 a well-known natural example, but also notably include the phages of important human bacterial diseases. Theory on hyperparasitism has mostly focused on their impact on the evolution of virulence of their parasite host and relatively little is known about evolutionary trajectories of hyperparasites themselves. Our general modeling framework highlights the central role the that ability of a hyperparasite to be transmitted with its parasite plays in their evolution. Hyperparasites which transmit with their parasite hosts (hitchhike) will be selected for lower virulence, trending towards hypermutualism or hypercommensalism and select against causing a reduction in parasite virulence (hypovirulence). We examine the impact on the evolution of hyperparasite systems a of a wide range of host and parasite traits showing, for example, that high parasite virulence selects for higher hyperparasite virulence feeding back into selection for hypovirulence in the parasite. Our results have implications for hyperparasite research, both as biocontrol agents and for understanding of how hyperparasites shape community ecology and evolution.


title: Cerebrovascular insulin receptors are defective in Alzheimer's disease

abstract:
Central response to insulin is suspected to be defective in Alzheimers disease (AD), but its localization in the brain remains unknown. While most insulin is secreted in the bloodstream by the pancreas, how it interacts with the blood-brain barrier (BBB) to alter brain function remains poorly defined.

Here, we show that human and murine cerebral insulin receptors (INSR), particularly the long isoform INSR-B, are concentrated in microvessels rather than in the parenchyma. Vascular concentrations of INSR-B were lower in the parietal cortex of subjects diagnosed with AD, positively correlating with cognitive scores, leading to a shift toward a higher INSR-A/B ratio, consistent with cerebrovascular insulin resistance in the AD brain. Vascular INSR was inversely correlated with {beta}-amyloid (A{beta}) plaques and {beta}-site APP cleaving enzyme 1 (BACE1), but positively correlated with insulin-degrading enzyme (IDE), neprilysin and ABCB1. Using brain cerebral intracarotid perfusion, we found that the transport rate of insulin across the BBB remained very low (<0.03 {micro}l.g-1.s-1) and was not inhibited by an INSR antagonist. However, intracarotid perfusion of insulin induced the phosphorylation of INSR{beta} which was restricted to microvessels. Such an activation of vascular INSR was blunted in 3xTg-AD mice, suggesting that AD neuropathology induces insulin resistance at the level of the BBB.

Overall, the present data in postmortem AD brains and an animal model of AD indicate that defects in the INSR localized at the BBB strongly contribute to brain insulin resistance in AD, in association with A{beta} pathology.

HighlightsO_LICirculating insulin activates brain insulin receptors in microvessels.
C_LIO_LIBBB INSR contribute to cerebral insulin resistance in AD.
C_LIO_LICognitive impairment in AD is associated with a loss of cerebrovascular INSR-B.
C_LIO_LILoss of isoform INSR-B is associated with increased BACE1 activity.
C_LI

SummaryLeclerc et al. show that circulating insulin activates cerebral insulin receptor localized on the blood-brain-barrier level (BBB), not in the parenchyma. Experiments with human brain samples and animal models provide evidence that INSR at the BBB are impaired in Alzheimers disease, thereby contributing to brain insulin resistance.


title: Tadr Is an Axonal Histidine Transporter Required for Visual Neurotransmission in Drosophila

abstract: Neurotransmitters are generated by de novo synthesis and are essential for sustained, high-frequency synaptic transmission. Histamine, a monoamine neurotransmitter, is synthesized through decarboxylation of histidine by Histidine decarboxylase (Hdc). However, little is known about how histidine is presented to Hdc as a precursor. Here, we identified a specific histidine transporter, TADR (Torn And Diminished Rhabdomeres), that is required for visual transmission in Drosophila. TADR and Hdc co-localized to neuronal terminals, and mutations in tadr reduced levels of histamine, thus disrupting visual synaptic transmission and phototaxis behavior. These results demonstrate that a specific amino acid transporter provides precursors for monoamine neurotransmitters, providing the first genetic evidence that a histidine amino acid transporter plays a critical role in synaptic transmission. These results suggest that TADR-dependent local de novo synthesis of histamine is required for synaptic transmission.


title: Single-cell Multiomics Reveals Clonal T-cell Expansions and Exhaustion in Blastic Plasmacytoid Dendritic Cell Neoplasm

abstract: The immune system represents a major barrier to cancer progression, driving the evolution of immunoregulatory interactions between malignant cells and T-cells in the tumor environment. Blastic plasmacytoid dendritic cell neoplasms (BPDCN), a rare acute leukemia with plasmacytoid dendritic cell (pDC) differentiation, provides a unique opportunity to study these interactions. pDCs are key producers of interferon alpha (IFNA) that play an important role in T-cell activation at the interface between the innate and adaptive immune system. To assess how uncontrolled proliferation of malignant BPDCN cells affects the tumor environment, we catalog immune cell heterogeneity in the bone marrow (BM) of five healthy controls and five BPDCN patients by analyzing 52,803 single-cell transcriptomes, including 18,779 T-cells. We test computational techniques for robust cell type classification and find that T-cells in BPDCN patients consistently upregulate interferon alpha (IFNA) response and downregulate tumor necrosis factor alpha (TNFA) pathways. Integrating transcriptional data with T-cell receptor sequencing via shared barcodes reveals significant T-cell exhaustion in BPDCN that is positively correlated with T-cell clonotype expansion. By highlighting new mechanisms of T-cell exhaustion and immune evasion in BPDCN, our results demonstrate the value of single-cell multiomics to understand immune cell interactions in the tumor environment.

category: immunology


title: Comparing management strategies for conserving communities of climate-threatened species with a stochastic metacommunity model

abstract: Many species are shifting their ranges to keep pace with climate change, but habitat fragmentation and limited dispersal could impede these range shifts. In the case of climate-vulnerable foundation species such as tropical reef corals and temperate forest trees, such limitations might put entire communities at risk of extinction. Restoring connectivity through corridors, stepping-stones, or enhanced quality of existing patches could prevent the extinction of several species, but dispersal-limited species might not benefit if other species block their dispersal. Alternatively, managers might relocate vulnerable species between habitats through assisted migration, but this is generally a species-by-species approach. To evaluate the relative efficacy of these strategies, we simulated the climate-tracking of species in randomized competitive metacommunities with alternative management interventions. We found that corridors and assisted migration were the most effective strategies at reducing extinction. Assisted migration was especially effective at reducing the extinction likelihood for short-dispersing species, but it often required moving several species repeatedly. Assisted migration was more effective at reducing extinction in environments with higher stochasticity, and corridors were more effective at reducing extinction in environments with lower stochasticity. We discuss the application of these approaches to an array of systems ranging from tropical corals to temperate forests.

category: ecology


title: Sentinel2GlobalLULC: A deep-learning-ready Sentinel-2 RGB image dataset for global land use/cover mapping

abstract: Land-Use and Land-Cover (LULC) mapping is relevant for many applications, from Earth system and climate modelling to territorial and urban planning. Global LULC products are continuously developing as remote sensing data and methods grow. However, there is still low consistency among LULC products due to low accuracy for some regions and LULC types. Here, we introduce Sentinel2GlobalLULC, a Sentinel-2 RGB image dataset, built from the consensus of 15 global LULC maps available in Google Earth Engine. Sentinel2GlobalLULC v1.1 contains 195572 RGB images organized into 29 global LULC mapping classes. Each image is a tile that has 224 x 224 pixels at 10 x 10 m spatial resolution and was built as a cloud-free composite from all Sentinel-2 images acquired between June 2015 and October 2020. Metadata includes a unique LULC type annotation per image, together with level of consensus, reverse geo-referencing, and global human modification index. Sentinel2GlobalLULC is optimized for the state-of-the-art Deep Learning models to provide a new gate towards building precise and robust global or regional LULC maps.


title: A mammalian herbivore prefers locally adapted populations in a common garden: implications for climate change mitigation

abstract:
O_LIClimate change is expected to alter habitat more rapidly than the pace of evolution, leading to tree populations that are maladapted to new local conditions. Assisted migration is a mitigation strategy that proposes preemptively identifying and planting genotypes that are robust to the expected climate change-induced alterations of an area. Assisted migration however, may impact the broader community, including herbivores which often coevolved with local plant genotypes and their defenses. Although this question has been examined in arthropod herbivores, few studies have assessed this question in mammalian herbivores, and fewer still have leveraged experimental design to disentangle the genetic contribution to herbivore preference.
C_LIO_LIWe examined the hypothesis that North American porcupine (Erethizon dorsatum) browsing on Fremont cottonwood (Populus fremontii) is under genetic control in a common garden, which allowed us to uncouple genetic and environmental contributions to browse preference.
C_LIO_LIGenerally, porcupines selected local trees and trees from climatically similar areas, where trees from local and cooler climate populations suffered over 2x more extensive herbivory than trees from warmer areas. Plant genotype was a significant factor for selection, with the most heavily browsed genotype having on average >10x more herbivory than the least heavily browsed. Because genotypes within and among populations were replicated, we calculated broad-sense heritability in which tree palatability by porcupines was H2B = 0.28 (95% CI: 0.13-0.48) among genotypes.
C_LIO_LISynthesis and applications. Our results indicate a genetic component to tree defenses against porcupine herbivory that can be predicted by the climate of the source population. This result has important implications for mammalian herbivores if climate change renders local tree genotypes maladaptive to new conditions. We recommend assisted migration efforts consider this implication and plant stock from both warmer and climatically similar areas to maintain genetic diversity in a changing environment, productivity and forage for mammalian herbivores.
C_LI


title: Environmental nucleic acids: a field-based comparison for monitoring freshwater habitats using eDNA and eRNA

abstract: Nucleic acids released by organisms and isolated from environmental substrates are increasingly being used for molecular biomonitoring. While environmental DNA (eDNA) has received attention recently, the potential of environmental RNA as a biomonitoring tool remains less explored. Several recent studies using paired DNA and RNA metabarcoding of bulk samples suggest that RNA might better reflect "metabolically active" parts of the community. However, such studies mainly capture organismal eDNA and eRNA. For larger eukaryotes, isolation of extra-organismal RNA will be important, but viability needs to be examined in a field-based setting. In this study we evaluate (a) whether extra-organismal eRNA release from macroeukaryotes can be detected given its supposedly rapid degradation, and (b) if the same field collection methods for eDNA can be applied to eRNA. We collected eDNA and eRNA from water in lakes where fish community composition is well documented, enabling a comparison between the two nucleic acids in two different seasons with monitoring using conventional methods. We found that eRNA is released from macroeukaryotes and can be filtered from water and metabarcoded in a similar manner as eDNA to reliably provide species composition information. eRNA had a small but significantly greater true positive rate than eDNA, indicating that it correctly detects more species known to exist in the lakes. Given relatively small differences between the two molecules in describing fish community composition, we conclude that if eRNA provides significant advantages in terms of lability, it is a strong candidate to add to the suite of molecular monitoring tools.


title: Attracting pollinators vs escaping herbivores: eco-evolutionary dynamics of plants confronted with an ecological trade-off

abstract: A large number of plant traits are subject to an ecological trade-off between attracting pollinators and escaping herbivores. The interplay of both plant-animal interactions determines their evolution. Within a plant-pollinator-herbivore community in which interaction strengths depend on trait-matching, eco-evolutionary dynamics are studied using the framework of adaptive dynamics. We characterize the type of selection acting on the plant phenotype and the consequences for multispecies coexistence. We find that pollination favors stabilizing selection and coexistence. In contrast, herbivory fosters runaway selection, which threatens plant-animal coexistence. These contrasting dynamics highlight the key role of ecological trade-offs in structuring ecological communities. In particular, we show that disruptive selection is possible when such trade-offs are strong. While the interplay of pollination and herbivory is known to maintain plant polymorphism in several cases, our work suggests that it might also have fueled the diversification process itself.


title: Folate pathway metabolites are altered in the plasma of subjects with Down syndrome: relation to chromosomal dosage

abstract: Down syndrome (DS) is the most common chromosomal disorder and it is caused by trisomy of chromosome 21 (Hsa21). Subjects with DS show a large heterogeneity of phenotypes and the most constant clinical features present are typical facies and intellectual disability (ID). Several studies demonstrated that trisomy 21 causes an alteration in the metabolic profile, involving among all one-carbon cycle. We performed enzyme-linked immunosorbent assays (ELISAs) to identify the concentration of 5 different intermediates of the one-carbon cycle, namely tetrahydrofolate (THF), 5-methyltetrahydrofolate (5-methyl-THF), 5-formyltetrahydrofolate (5-formyl-THF), S-adenosyl-homocysteine (SAH) and S-adenosyl-methionine (SAM) in plasma samples obtained from a total of 164 subjects with DS compared to 54 euploid subjects. Results highlight specific alterations of THF with a median concentration ratio DS/control of 2:3, a decrease of a necessary molecule perfectly consistent with a chromosomal dosage effect. Moreover, SAM and SAH show a ratio of 2:1 and 3.6:1, respectively. The relevance of these results for the biology of intelligence and its impairment in trisomy 21 is discussed, leading to the final proposal of 5-methyl-THF as the best candidate for a clinical trial aimed at restoring the dysregulation of one-carbon cycle in trisomy 21, possibly improving cognitive skills of subjects with DS.

category: genetics


title: One-carbon pathway metabolites are altered in the plasma of subjects with Down syndrome: relation to chromosomal dosage


title: Glucocorticoids Unmask Silent Non-Coding Genetic Risk Variants for Common Diseases

abstract: Understanding the function of non-coding genetic variants represents a formidable challenge for biomedicine. We previously identified genetic variants that influence gene expression only after exposure to a hormone or drug. Using glucocorticoid signaling as a model system, we have now demonstrated, in a genome-wide manner, that exposure to glucocorticoids triggered disease risk variants with previously unclear function to influence the expression of genes involved in autoimmunity, metabolic and mood disorders, osteoporosis and cancer. Integrating a series of pharmacogenomic and pharmacoepigenomic datasets, we identified the cis-regulatory elements and 3-dimensional interactions underlying the ligand-dependent associations between those genetic variants and distant risk genes. These observations increase our understanding of mechanisms of non-coding genetic variant-chemical environment interactions and advance the fine-mapping of disease risk and pharmacogenomic loci.


title: Experimental sound exposure modifies swimming activities and increases food handling error in zebrafish (Danio rerio)

abstract: Anthropogenic sound is globally increasing and is recognized as a source of environmental pollution in terrestrial and aquatic habitats. Sound is an important sensory stimulus for aquatic organisms and it may cause fluctuations in stress-related physiological indices and in a broader extent induce behavioural effects in a range of marine and freshwater fishes. However sound exposure may also induce changes in swimming activities, feed efficiency and productivity of available food sources in fish. Here, we experimentally tested sound effects on swimming activities and foraging performance in thirty adult Zebrafish (Danio rerio) individually in captivity. We used adult zebrafish and water flea (Daphnia magna) as model predator and prey, respectively. In terms of acoustic stimuli, we used four sound treatments with different temporal patterns (all in the same frequency range and moderate exposure level). Our results constitute strong evidence for sound-related effects on zebrafish behaviour. All sound treatments led to a significant increase in the number of startle response, brief and prolonged swimming speed for zebrafish (P<0.05). We found partially brief and prolonged sound effects on the spatial distribution of zebrafish; Although there were not any significant sound-related changes for horizontal spatial displacement in all treatments (P>0.05), zebrafish swam significantly more in the lower layer of the tank except for irregular intermittent 1:1-7 in brief sound exposure (P<0.05). The results of foraging performance showed that food discrimination error unaffected by sound treatments and was low for the zebrafish (P>0.05). However, food handling error was affected by sound treatments; all treatments induced a significant rise in handling error (P<0.001). This study highlights the impact of sound on zebrafish swimming activities, and that more feeding bouts are needed to consume the same number of food items increasing energy demand under noisy conditions.

category: animal behavior and cognition


title: Rethinking Margin of Stability: Incorporating Step-To-Step Regulation to Resolve the Paradox

abstract: Maintaining frontal-plane stability is a major objective of human walking. Derived from inverted pendulum dynamics, the mediolateral Margin of Stability (MoSML) is frequently used to measure peoples frontal-plane stability on average. However, typical MoSML-based analyses deliver paradoxical interpretations of stability status. To address mediolateral stability using MoSML, we must first resolve this paradox. Here, we developed a novel framework that unifies the well-established inverted pendulum model with Goal-Equivalent Manifold (GEM)-based analyses to assess how humans regulate step-to-step balance dynamics to maintain mediolateral stability. We quantified the extent to which people corrected fluctuations in mediolateral center-of-mass state relative to a MoSML-defined candidate stability GEM in the inverted pendulum phase plane. Participants variability and step-to-step correction of tangent and perpendicular deviations from the candidate stability GEM demonstrate that regulation of balance dynamics involves more than simply trying to execute a constant-MoSML balance control strategy. Participants adapted these step-to-step corrections to mediolateral sensory and mechanical perturbations. How participants regulated mediolateral foot placement strongly predicted how they regulated center-of-mass state fluctuations, suggesting that regulation of center-of-mass state occurs as a biomechanical consequence of foot placement regulation. We introduce the Probability of Instability (PoI), a convenient statistic that accounts for step-to-step variance to properly predict instability likelihood on any given future step. Participants increased lateral PoI when destabilized, as expected. These lateral PoI indicated an increased risk of lateral instability, despite larger (i.e., more stable) average MoSML. PoI thereby explicitly predicts instability risk to decisively resolve the existing paradox that arises from conventional MoSML implementations.

category: bioengineering


title: No part gets left behind: Tiled nanopore sequencing of whole ASFV genomes stitched together using Lilo

abstract: African Swine Fever virus (ASFV) is the causative agent of a deadly, panzootic disease, infecting wild and domesticated suid populations. Contained for a long time to the African continent, an outbreak of a particularly infectious variant in Georgia in 2007 initiated the spread of the virus around the globe, severely impacting pork production and local economies. The virus is highly contagious and has a mortality of up to 100% in domestic pigs. It is critical to track the spread of the virus, detect variants associated with pathology, and implement biosecurity measures in the most effective way to limit its spread. Due to its size and other limitations, the 170-190kbp large DNA virus has not been well sequenced with fewer than 200 genome sequences available in public repositories. Here we present an efficient, low-cost method of sequencing ASFV at scale. The method uses tiled PCR amplification of the virus to achieve greater coverage, multiplexability and accuracy on a portable sequencer than achievable using shotgun sequencing. We also present Lilo, a pipeline for assembling tiled amplicon data from viral or microbial genomes without relying on polishing against a reference, allowing for structural variation and hypervariable region assembly other methods fail on. The resulting ASFV genomes are near complete, lacking only parts of the highly repetitive 3- and 5telomeric regions, and have a high level of accuracy. Our results will allow sequencing of ASFV at optimal efficiency and high throughput to monitor and act on the spread of the virus.


title: A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

abstract:
The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.

Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the users unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.

Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.


title: Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin

abstract: The development of chemoresistance remains a significant cause of treatment failure in breast cancer. We posit that a mathematical understanding of chemoresistance could assist in developing successful treatment strategies. Towards that end, we have developed a model that describes the effects of the standard chemotherapeutic drug doxorubicin on the MCF-7 breast cancer cell line. We assume that the tumor is composed of two subpopulations: drug-resistant cells, which continue proliferating after treatment, and drug-sensitive cells, which gradually transition from proliferating to treatment-induced death. The model is fit to experimental data including variations in drug concentration, inter-treatment interval, and number of doses. Our model recapitulates tumor growth dynamics in all these scenarios (as quantified by the concordance correlation coefficient, CCC > 0.95). In particular, superior tumor control is observed with higher doxorubicin concentrations, shorter inter-treatment intervals, and a higher number of doses (p < 0.05). Longer inter-treatment intervals require adapting the model parameterization after each doxorubicin dose, suggesting the promotion of chemoresistance. Additionally, we propose promising empirical formulas to describe the variation of model parameters as functions of doxorubicin concentration (CCC > 0.78). Thus, we conclude that our mathematical model could deepen our understanding of the effects of doxorubicin and could be used to explore practical drug regimens achieving optimal tumor control.

category: cancer biology


title: A 3D printable device allowing fast and reproducible longitudinal preparation of mouse intestines

abstract: Accurate and reproducible analysis of mouse small and large intestinal lumen is key for research involving intestinal pathology in preclinical models. Currently, there is no easily accessible, standardized method that allows researchers of different skill levels to consistently dissect intestines in a time-efficient manner. Here, we describe the design and use of the 3D printed "Mouse Intestinal Slicing Tool" (MIST), which can be used to longitudinally prepare murine intestines for further analysis. We benchmarked the MIST against a commonly used procedure involving scissors to make a longitudinal cut along the intestines. Use of the MIST halved the time per mouse to prepare the intestines and outperformed alternative methods in smoothness of the cutting edge and general reproducibility. By sharing the plans for printing the MIST, we hope to contribute a uniformly applicable method for saving time and increasing consistency in studies of the mouse gastrointestinal tract.

category: pathology


title: Evaluation of the efficacy of simethicone in the abdominal ultrasound and pancreas evaluation on dogs

abstract: Intestinal gas results in low quality imaging in abdominal ultrasound in domestic animals. On dogs, suggested preparation protocols are varied and low studied. The aim of this work was comparing the efficacy between two preparations in improving the complete abdominal ultrasound exam and pancreas preview. 40 dogs were enrolled in this study. They were separated in two groups (NS diet: fasting; WS diet: fasting added to simethicone). The pancreas images were taken from left lateral decubitus. A score of one to three (1: bad, 2: fair and 3: good) measured separately the quality of the complete exam, left and right limbs and pancreatic body. In both treatments, there were results above 50% of good images of the complete exam and right limb of the pancreas. Otherwise, there were results above 90% of bad images of the right limb and pancreatic body. According to the fact of there is no statistically significant difference between the diets, as well submitted animals to the NS diet as the WS diet, all the results obtained from this work (bad or good images) could be acquired from any of both diets. The good abdominal exam preview as well submitted animals to the simethicone as those without the medication refute this medicine requirement to the abdominal ultrasound exam, but not to the evaluation of the left limb and pancreatic body.

category: pharmacology and toxicology


title: Stomata Detector: High-throughput automation of stomata counting in a population of African rice (Oryza glaberrima) using transfer learning.

abstract: Stomata are dynamic structures that control the gaseous exchange of CO2 from the external to internal environment and water loss through transpiration. The density and morphology of stomata have important consequences in crop productivity and water use efficiency, both are integral considerations when breeding climate change resilient crops. The phenotyping of stomata is a slow manual process and provides a substantial bottleneck when characterising phenotypic and genetic variation for crop improvement. There are currently no open-source methods to automate stomatal counting. We used 380 human annotated micrographs of O. glaberrima and O. sativa at x20 and x40 objectives for testing and training. Training was completed using the transfer learning for deep neural networks method and R-CNN object detection model. At a x40 objective our method was able to accurately detect stomata (n = 540, r = 0.94, p<0.0001), with an overall similarity of 99% between human and automated counting methods. Our method can batch process large files of images. As proof of concept, characterised the stomatal density in a population of 155 O. glaberrima accessions, using 13,100 micrographs. Here, we present developed Stomata Detector; an open source, sophisticated piece of software for the plant science community that can accurately identify stomata in Oryza spp., and potentially other monocot species.

category: plant biology


title: Efficiently, accurately, intelligently dissecting bamboo: characteristic of vascular bundle in Phyllostachys

abstract:
A comprehensive understanding of vascular bundles is the key to elucidate the excellent intrinsic mechanical properties of bamboo. This research aims to investigate the gradient distribution of fiber volume fraction and the gradient changes in the shape of vascular bundles along the radial axis in Phyllostachys. We constructed a universal transfer-learning-based vascular bundle detection model with high precision of up to 96.97%, which can help to acquire the characteristics of vascular bundles quickly and accurately. The total number of vascular bundles, total fiber sheath area, the length, width and area of fiber sheath of individual vascular bundles within the entire cross-section were counted, and the results showed that these parameters had a strongly positive linear correlation with the outer circumference and wall thickness of bamboo culms, but the fiber volume fraction (around 25.5 %) and the length-to-width ratio of the vascular bundles (around 1.226) were relatively constant. Furthermore, we layered the cross section of bamboo according to the wall thickness finely and counted the characteristics of vascular bundle in each layer. The results showed that the radial distribution of fiber volume fraction decreased exponentially, the radial distribution of the length-to-width ratio of vascular bundle decreased quadratically, the radial distribution of the width of vascular bundle increased linearly. The trends of the gradient change in vascular bundles characteristics were found highly consistent among 29 bamboo species in Phyllostachys.

One sentence summaryA universal vascular bundle detection model can efficiently dissect vascular bundles in Phyllostachys, and the radial gradient change of vascular bundles in cross-section are found highly consistent.


title: Dietary and serum tyrosine, white matter microstructure and inter-individual variability in executive functions in overweight adults: relation to sex/gender and age

abstract:
Tyrosine (tyr), the precursor of the neurotransmitter dopamine, is known to modulate cognitive functions including executive attention. Tyr supplementation is suggested to influence dopamine-modulated cognitive performance. However, results are inconclusive, regarding the presence or strength and also the direction of the association between tyr and cognitive function. This pre-registered cross-sectional analysis investigates whether diet-associated serum tyr relates to executive attention performance, and whether this relationship is moderated by differences in white matter microstructure. 59 healthy, overweight, young to middle-aged adults (20F, 28.3 {+/-} 6.6 years, BMI: 27.3 {+/-} 1.5 kg/m2) drawn from a longitudinal study reported dietary habits, donated blood and completed diffusion-weighted brain magnetic resonance imaging and the attention network test. Main analyses were performed using linear regressions and non-parametric voxel-wise inference testing.

Confirmatory analyses did neither support an association between dietary and serum tyr nor a relationship between relative serum tyr/large neutral amino acids (LNAA) levels or white matter microstructure and executive attention performance. However, exploratory analyses revealed higher tyr intake, higher serum tyr and better executive attention performance in the male sex/gender group. In addition, older age was associated with higher dietary tyr intake and lower fractional anisotropy in a widespread cluster across the brain. Finally, a positive association between relative serum tyr/LNAA and executive attention performance was found in the male sex/gender group when accounting for age effects.

Our analysis advances the field of dopamine-modulated cognitive functions by revealing sex/gender and age differences which might be diet-related. Longitudinal or intervention studies and larger sample sizes are needed to provide more reliable evidence for links between tyr and executive attention.


title: Multivariate autoregressive model estimation for high dimensional intracranial electrophysiological data

abstract: Fundamental to elucidating the functional organization of the brain is the assessment of causal interactions between different brain regions. Multivariate autoregressive (MVAR) modeling techniques applied to multisite electrophysiological recordings are a promising avenue for identifying such causal links. They estimate the degree to which past activity in one or more brain regions is predictive of another regions present activity, while simultaneously accounting for the mediating effects of other regions. Including in the model as many mediating variables as possible has the benefit of drastically reducing the odds of detecting spurious causal connectivity. However, effective bounds on the number of MVAR model coefficients that can be estimated reliably from limited data make exploiting the potential of MVAR models challenging. Here, we utilize well-established dimensionality-reduction techniques to fit MVAR models to human intracranial data from {bsim}100 - 200 recording sites spanning dozens of anatomically and functionally distinct cortical regions. First, we show that high dimensional MVAR models can be successfully estimated from long segments of data and yield plausible connectivity profiles. Next, we use these models to generate synthetic data with known ground-truth connectivity to explore the utility of applying principal component analysis and group least absolute shrinkage and selection operator (LASSO) to reduce the number of parameters (connections) during model fitting to shorter data segments. We show that group LASSO is highly effective for recovering ground truth connectivity in the limited data regime, capturing important features of connectivity for high-dimensional models with as little as 10 s of data. The methods presented here have broad applicability to the analysis of high-dimensional time series data in neuroscience, facilitating the elucidation of the neural basis of sensation, cognition, and arousal.


title: Imaging Three-Dimensional Brain Organoid Architecture from Meso- to Nanoscale across Development

abstract:
Organoids are human stem cell-derived three-dimensional cultures offering a new avenue to model human development and disease. Brain organoids allow studying various aspects of human brain development in the finest details in vitro in a tissue-like context. However, spatial relationships of subcellular structures such as synaptic contacts between distant neurons are hardly accessible by conventional light microscopy. This limitation can be overcome by systems that quickly image the entire organoid in three dimensions and in super-resolution. To that end we have developed a setup combining tissue expansion and light sheet fluorescence microscopy for imaging and quantifying diverse spatial parameters during organoid development. This technique enables zooming from a mesoscopic perspective into super-resolution within a single imaging session, thus revealing cellular and subcellular structural details in three spatial dimensions, including unequivocal delineation of mitotic cleavage planes as well as the alignment of pre- and postsynaptic proteins. We expect light sheet fluorescence expansion microscopy (LSFEM) to facilitate qualitative and quantitative assessment of organoids in developmental and disease-related studies.

Summary statementThe combination of light sheet fluorescence and expansion microscopy enables imaging of mature human brain organoids in toto and down to synaptic resolution


title: Baseline Shift in Neuronal Oscillations and Its Implications for the Interpretation of Evoked Activity Obtained with EEG/MEG

abstract: Oscillations and evoked responses are two main types of neuronal activity recorded non-invasively with EEG/MEG. Although typically studied separately, they might in fact represent the same neuronal process. One possibility to unite them is to demonstrate that neuronal oscillations have non-zero mean which would indicate that stimulus- or task-triggered amplitude modulation of oscillations will unavoidably lead to the generation of evoked responses. We validated this mechanism using computational modelling and analysis of a large EEG data set. With a biophysical model, we indeed demonstrated that the mean of alpha oscillations is non-zero for a wide range of model parameters. In EEG data we detected non-zero mean alpha oscillations in about 96% of the participants. Furthermore, using complementary neuronal-ensemble modelling, we provided an explanation for the previously observed discrepancies between evoked responses and oscillatory amplitude changes after stimulus presentation. Overall, our results provide strong support for the unification of neuronal oscillations and evoked responses.


title: Non-zero Mean Alpha Oscillations are Evident in Computational Model and Empirical Data


title: Sex-dependent changes in murine striatal dopamine release, sleep, and behavior during spontaneous Δ-9-tetrahydrocannabinol abstinence

abstract: Withdrawal symptoms are observed upon cessation of cannabis use in humans. Although animal studies have examined withdrawal symptoms following exposure to delta-9-tetrahydrocannabinol (THC), difficulties in obtaining objective measures of spontaneous withdrawal using paradigms that mimic cessation of use in humans have slowed research. The neuromodulator dopamine (DA) is known to be affected by chronic THC treatment and plays a role in many behaviors related to human THC withdrawal symptoms. These symptoms include sleep disturbances that often drive relapse, and emotional behaviors, e.g., irritability and anhedonia. We examined THC withdrawal-induced changes in striatal DA release and the extent to which sleep disruption and behavioral maladaptation manifest during withdrawal in a mouse chronic cannabis exposure model. Using a THC treatment regimen known to produce tolerance we measured electrically elicited DA release in acute brain slices from different striatal subregions during early and late THC abstinence. Long-term polysomnographic recordings from mice were used to assess vigilance state and sleep architecture before, during, and after THC treatment. We additionally assessed how behaviors that model human withdrawal symptoms are altered by chronic THC treatment in early and late abstinence. We detected altered striatal DA release, sleep disturbances that mimic clinical observations, and behavioral maladaptation in mice following tolerance inducing THC treatment. Sex differences were observed in nearly all metrics. Altered striatal DA release, sleep and affect-related behaviors associated with spontaneous THC abstinence were more consistently observed in male mice. To our knowledge these findings provide the first model of directly translatable non-precipitated cannabis withdrawal symptoms, in particular, sleep disruption.


title: Regional Topological Aberrances of White Matter- and Gray Matter-based Functional Networks for Attention Processing may Foster Traumatic Brain Injury-Related Attention Deficits in Adults

abstract: Traumatic brain injury (TBI) is highly prevalent in adults. TBI-related functional brain alterations have been linked with common post-TBI neurobehavioral sequelae, with unknown neural sub-strates. This study examined the systems-level functional brain alterations in white matter (WM) and gray matter (GM) for visual sustained attention processing, their interactions, and contribution to post-TBI attention deficits. Task-based functional MRI data were collected from 42 adults with TBI and 43 group-matched normal controls (NCs), and analyzed using the graph theoretic tech-nique. Global and nodal topological properties were calculated and compared between the two groups. Correlation analyses were conducted between the neuroimaging measures that showed significant between-group differences and the behavioral symptom measures in attention domain in the groups of TBI and NCs, respectively. Significantly altered nodal efficiency and/or degree in several WM and GM nodes were reported in the TBI group, including the posterior corona radiata (PCR), posterior thalamic radiation (PTR), postcentral gyrus (PoG), and superior temporal sulcus (STS). Subjects with TBI also demonstrated abnormal systems-level functional synchronization between the PTR and STS in the right hemisphere, hypo-interaction between PCR and PoG in the left hemisphere; as well as the involvement of systems-level functional aberrances in PCR in TBI-related behavioral impairments in the attention domain. Findings of the current study suggest that TBI-related systems-level functional alterations associated with these two major association WM tracts and their anatomically connected GM regions may play critical role in TBI-related behavioral deficits in attention domain.


title: Dopaminergic challenge dissociates learning from primary versus secondary sources of information

abstract: Some theories of human cultural evolution posit that humans have social-specific learning mechanisms that are adaptive specialisations moulded by natural selection to cope with the pressures of group living. However, the existence of neurochemical pathways that are specialised for learning from social information and from individual experience is widely debated. Cognitive neuroscientific studies present mixed evidence for social-specific learning mechanisms: some studies find dissociable neural correlates for social and individual learning whereas others find the same brain areas and, dopamine-mediated, computations involved in both. Here we demonstrate that, like individual learning, social learning is modulated by the dopamine D2 receptor antagonist haloperidol when social information is the primary learning source, but not when it comprises a secondary, additional element. Two groups (total N = 43) completed a decision-making task which required primary learning, from own experience, and secondary learning from an additional source. For one group the primary source was social, and secondary was individual; for the other group this was reversed. Haloperidol affected primary learning irrespective of social/individual nature, with no effect on learning from the secondary source. Thus, we illustrate that neurochemical mechanisms underpinning learning can be dissociated along a primary-secondary but not a social-individual axis. These results resolve conflict in the literature and support an expanding field showing that, rather than being specialised for particular inputs, neurochemical pathways in the human brain can process both social and non-social cues and arbitrate between the two depending upon which cue is primarily relevant for the task at hand.


title: Systemic lipid peroxidation and skeletal tissues metabolism in animals with simulated posttraumatic osteoarthrosis

abstract:
The role of individual factors in the progressing of degenerative and dystrophic changes of articular cartilage as the focus of pathologic changes in posttraumatic osteoarthrosis (PTOA) has been studied comprehensively. However, no single concept of pathogenetic mechanisms leading to the formation of permanent changes in the affected joint has been represented yet. Therefore, the investigation of lipid peroxidation and skeletal tissues metabolism in animals with simulated PTOA is a challenging and important issue.

In 28 non-linear male rats (12 intact control animals and 16 experimental animals with simulated knee OA) we studied the lipid peroxidation rate by the level of lipid hydroperoxides, antioxidant system activity by the indicants of total antioxidant, and thiol statuses. The destruction processes in skeletal tissues were evaluated by the level of hyaluronan, a cartilaginous tissue marker, and subchondral bone turnover makers (fibroblast growth factor-23, osteoprotegerin, sclerostin, osteocalcin).

In rats with simulated PTOA, we observed the activation of lipid peroxidation with the accumulation of lipid hydroperoxides in systemic blood flow along with the insignificant decrease of thiol status indicant while the normal antioxidant activity is maintained. We also revealed the significant increase of biopolymer hyaluronan (p<0.05) in a negative change of turnover regulation marker (the significant increase in fibroblast growth factor-23 (p<0.05) with the emerging trend for osteoprotegerin and sclerostin decrease) and bone formation marker (high osteocalcin) as compared to the intact controls.

Our findings confirmed that animals with simulated PTOA featured rearranging of skeletal tissues as compared to intact animals. This process involved degenerative destruction of both chondral and osseous tissues along with profound prooxidant activity and relative incompetence of the thiol system while the indicants of general antioxidant activity remain normal. This suggests the importance of the analyzed markers in PTOA pathogenesis and determined the prospects of their use for the evaluation of therapy efficacy.

category: microbiology


title: A family of fitness landscapes modeled through gene regulatory networks

abstract: Over 100 years, Fitness landscapes have been a powerful metaphor for understanding the evolution of biological systems. These landscapes describe how genotypes are connected to each other and are related according to relative fitness. Despite the high dimensionality of such real-world landscapes, empirical studies are often limited in their ability to quantify the fitness of different genotypes beyond point mutations, while theoretical works attempt statistical/mechanistic models to reason the overall landscape structure. However, most classical fitness landscape models overlook an instinctive constraint that genotypes leading to the same phenotype almost certainly share the same fitness value, since the information of genotype-phenotype mapping is rarely incorporated. Here, we investigate fitness landscape models through the lens of Gene Regulatory Networks (GRNs), where the regulatory products are computed from multiple genes and collectively treated as the phenotypes. With the assumption that regulatory mediators/products exhibit binary states, we prove topographical features of GRN fitness landscape models such as accessibility and connectivity insensitive to the choice of the fitness function. Furthermore, using graph theory, we deduce a mesoscopic structure underlying GRN fitness landscape models that retains necessary information for evolutionary dynamics with minimal complexity. We also propose an algorithm to construct such a mesoscopic backbone which is more efficient than the brute-force approach. Combined, this work provides mathematical implications for fitness landscape models with high-dimensional genotype-phenotype mapping, yielding the potential to elucidate empirical landscapes and their resulting evolutionary processes in a manner complementary to existing computational studies.


title: A framework for defining livestock ecotypes based on ecological modelling and exploring genomic environmental adaptation: the example of Ethiopian village chicken

abstract: In evolutionary ecology, an ecotype is a population that is genetically adapted to specific environmental conditions. Environmental and genetic characterisation of livestock ecotypes can play a crucial role in conservation and breeding improvement, particularly to achieve climate resilience. However, livestock ecotypes are often arbitrarily defined without a detailed characterisation of their agro-ecologies. In this study, we employ a novel integrated approach, combining Ecological Niche Modelling (ENM) with genomics, to delineate ecotypes based on environmental characterisation of population habitats and unravel the signatures of adaptive selection in the ecotype genomes. The method was applied on 25 Ethiopian village chicken populations representing diverse agro-climatic conditions. ENM identified six key environmental drivers of adaptation and delineated 12 ecotypes. Within- ecotype selection signature analyses (using Hp and iHS methods) identified 1,056 candidate sweep regions (SRs) associated with diverse biological processes. A few biological pathways were shared amongst most ecotypes and the involved genes showed functions important for scavenging chickens, e.g. neuronal development/processes, immune response, vision development, and learning. Genotype-environment association using Redundancy Analysis (RDA) allowed for correlating [~]33% of the SRs with major environmental drivers. Inspection of some strong candidate genes from selection signature analysis and RDA showed highly relevant functions in relation to the major environmental drivers of corresponding ecotypes. This integrated approach offers a powerful tool to gain insight into the complex processes of adaptive evolution including the genotype x environment (GxE) interactions.


title: DeepPLA: a novel deep learning-based model for protein-ligand binding affinity prediction

abstract: The substantial cost of new drug research and development has consistently posed a huge burden and tremendous challenge for both pharmaceutical companies and patients. In order to lower the expenditure and development failure rate, repurposing existing and approved drugs and identifying novel interactions between the drug molecules and the target proteins based on computational methods have gained growing attention. Here, we propose the DeepPLA, a novel deep learning-based model that combines ResNet-based 1D CNN and biLSTM, to establish an end-to-end network for protein-ligand binding affinity prediction. We first apply pre-trained embedding methods to encode the raw drug molecular SMILES strings and target protein sequences into dense vector representations. The dense vector representations separately go through ResNet-based 1D CNN modules to derive features. The extracted feature vectors are concatenated and further fed into the biLSTM network after average pooling operation, followed by the MLP module to finally predict binding affinity. We used BindingDB dataset for training and evaluating our DeepPLA model. The result shows that the DeepPLA model reaches a good performance for the protein-ligand binding affinity prediction in terms of R, RMSE, MAE, R2 and MSE with 0.89, 0.68, 0.50, 0.79 and 0.46 on the training set; and scores 0.84, 0.80, 0.60, 0.71 and 0.64 on the independent testing set, respectively. This result suggests the high accuracy of the DeepPLA prediction performance, as well as its high capability in generalization, demonstrating that the DeepPLA can be the potential upgrade to pinpoint new drug-target interactions to find better destinations for proven drugs.


title: yHydra: Deep Learning enables an Ultra Fast Open Search by Jointly Embedding MS/MS Spectra and Peptides of Mass Spectrometry-based Proteomics

abstract:
Mass spectrometry-based proteomics allows to study all proteins of a sample on a molecular level. The ever increasing complexity and amount of proteomics MS-data requires powerful and yet efficient computational and statistical analysis. In particular, most recent bottom-up MS-based proteomics studies consider either a diverse pool of post-translational modifications, employ large databases - as in metaproteomics or proteogenomics, contain multiple isoforms of proteins, include unspecific cleavage sites or even combinations thereof and thus face a computationally challenging situation regarding protein identification. In order to cope with resulting large search spaces, we present a deep learning approach that jointly embeds MS/MS spectra and peptides into the same vector space such that embeddings can be compared easily and interchangeable by using euclidean distances. In contrast to existing spectrum embedding techniques, ours are learned jointly with their respective peptides and thus remain meaningful. By visualizing the learned manifold of both spectrum and peptide embeddings in correspondence to their physicochemical properties our approach becomes easily interpretable. At the same time, our joint embeddings blur the lines between spectra and protein sequences, providing a powerful framework for peptide identification. In particular, we build an open search, which allows to search multiple ten-thousands of spectra against millions of peptides within seconds. yHydra achieves identification rates that are compatible with MSFragger. Due to the open search, delta masses are assigned to each identification which allows to unrestrictedly characterize post-translational modifications. Meaningful joint embeddings allow for faster open searches and generally make downstream analysis efficient and convenient for example for integration with other omics types.

Availability(under MIT license) https://github.com/tzom/yHydra

Contactbernhard.renard@hpi.de


title: A novel Phytophthora sojae effector PsFYVE1 modulates transcription and alternative splicing of immunity related genes by targeting host RZ-1A protein

abstract:
Oomycete pathogens secrete many effectors to manipulate plant immunity and promote infection. However, relatively few effector types have been well characterized. In this study, members of a FYVE domain-containing protein family that is highly expanded in oomycetes were systematically identified, and one secreted protein, PsFYVE1, was selected for further study. PsFYVE1 enhanced Phytophthora infection in Nicotiana benthamiana and was necessary for P. sojae virulence. The FYVE domain of PsFYVE1 had PI3P-binding activity that depended on four conservative amino acid residues. Furthermore, PsFYVE1 targeted RNA-binding proteins RZ-1A/1B/1C in N. benthamiana and soybean, and silencing of NbRZ-1A/1B/1C genes attenuates plant immunity. NbRZ-1A was associated with spliceosome that included three important components, NbGRP7, NbGRP8, and NbU1-70K. Notably, PsFYVE1 could disrupt NbRZ-1A-NbGRP7 interaction. RNA-seq and subsequent experimental analysis demonstrated that PsFYVE1 and NbRZ-1A not only co-regulated transcription of NbHCT, NbEIN2, and NbSUS4 genes but also modulated pre-mRNA alternative splicing (AS) of the NbNSL1 gene, which participated in plant immunity. Collectively, these findings indicate that the FYVE domain-containing protein family includes potential new effector types and also highlight that plant pathogen effectors can regulate plant immunity related genes at both transcription and AS levels to promote disease.

Author summaryMany plant pathogenic oomycetes secrete effector proteins into plants to facilitate infection. Discovering potential repertoire of novel effectors and corresponding molecular mechanisms are major themes in the study of oomycete-plant interactions. Here, we characterized a FYVE domain-containing protein (PsFYVE1) in P. sojae. PsFYVE1 carries a functional secretory signal peptide and is a virulence-essential effector for P. sojae infection. We demonstrated that PsFYVE1 interacted with a class of plant RNA-binding proteins, including soybean GmRZ-1A/1B/1C and N. benthamiana NbRZ-1A/1B/1C. Silencing of NbRZ-1A/1B/1C proteins increased Phytophthora infection and suppressed plant defense. Furthermore, NbRZ-1A interacted with the spliceosome components, and PsFYVE1 disrupted association between NbRZ-1A and spliceosome component NbGRP7. We examined the global transcription and alternative splicing (AS) changes regulated by PsFYVE1 and NbRZ-1A, which indicated that PsFYVE1 and NbRZ-1A co-regulated transcription and pre-mRNA AS of immunity-related genes. Thus, this study identifies a novel virulence-related effector from P. sojae and a class of positive regulators of plant immunity, and reveals a detailed mechanism of effector-medicated transcription and AS regulation during pathogen-plant interactions.


title: Serum Amyloid A promotes Acetaminophen-induced liverinjury by damaging sinusoidal endothelial cell and exacerbating platelet aggregation in liver

abstract:
BackgroundAcetaminophen (APAP) is the most commonly used non-prescription antipyretic and analgesic drugs. Overuse of APAP can cause hepatotoxicity. Liver sinusoidal endothelial cells (LSECs) damage is an important early event in APAP-induced liver injury. Serum amyloid A (SAA) is an acute phase protein that mainly produced by hepatocytes, and promotes endothelial dysfunction via a pro-inflammatory and pro-thrombotic effect in atherosclerosis and renal disease. However, the role of SAA in APAP-induced liver injury remains unclear.

MethodsIn this study, we used neutralizing antibody (anti-SAA) or antagonistic small peptide derived from sequence of human SAA1/2 (SAA-pep) to block the functional activity of Saa1/2 in mouse serum. Immunohistochemistry staining, Evans blue and platelet adhesion assays were performed to examine the liver damage, the integrity of sinusoidal endothelium and platelets accumulation in APAP-induce liver injury.

ResultsOur study showed that in the early stage of APAP-induced acute liver injury in mice, the intrahepatic and serum Saa1/2 levels were significantly increased within 24 hours, and then gradually reduced to normal level from 3 days. Neutralization of Saa1/2 by antibodies or peptides effectively prevented the destruction of hepatic sinusoids, reduced the intrahepatic hemorrhage and platelet accumulation in liver, as well as increased the survival rate of mice treated with lethal dose of APAP. In vitro experiments showed that Saa1/2 aggravated LSECs death induced by APAP. Moreover, Saa1/2 promoted platelets adhesion on LSECs via Tlr2/Vcam-1 axis.

ConclusionOur findings suggest that Saa1/2 promotes APAP-induced liver injury by damaged LSECs and exacerbated platelets aggregation. This study provides a potential target for intervention of acute liver injury/failure caused by hepatotoxic drugs such as APAP.


title: Combining deep learning and automated feature extraction to analyze minirhizotron images: development and validation of a new pipeline

abstract: Root systems of crops play a significant role in agro-ecosystems. The root system is essential for water and nutrient uptake, plant stability, symbiosis with microbes and a good soil structure. Minirhizotrons, consisting of transparent tubes that create windows into the soil, have shown to be effective to non-invasively investigate the root system. Root traits, like root length observed around the tubes of minirhizotron, can therefore be obtained throughout the crop growing season. Analyzing datasets from minirhizotrons using common manual annotation methods, with conventional software tools, are time consuming and labor intensive. Therefore, an objective method for high throughput image analysis that provides data for field root-phenotyping is necessary. In this study we developed a pipeline combining state-of-the-art software tools, using deep neural networks and automated feature extraction. This pipeline consists of two major components and was applied to large root image datasets from minirhizotrons. First, a segmentation by a neural network model, trained with a small image sample is performed. Training and segmentation are done using "Root-Painter". Then, an automated feature extraction from the segments is carried out by "RhizoVision Explorer". To validate the results of our automated analysis pipeline, a comparison of root length between manually annotated and automatically processed data was realized with more than 58,000 images. Mainly the results show a high correlation (R=0.81) between manually and automatically determined root lengths. With respect to the processing time, our new pipeline outperforms manual annotation by 98.1 - 99.6 %. Our pipeline,combining state-of-the-art software tools, significantly reduces the processing time for minirhizotron images. Thus, image analysis is no longer the bottle-neck in high-throughput phenotyping approaches.


title: No evidence that LSD microdosing affects recall or the balance between distracter resistance and updating

abstract: The effect of low doses (<=20 g) of LSD on working memory, in the absence of altered states of consciousness, remain largely unexplored. Given its possible effects on serotonin 5-HT2A receptors and dopaminergic signalling, it could be hypothesised that LSD microdoses modulate working memory recall. Moreover, in line with computational models, LSD microdoses could exert antagonistic effects on distracter resistance and updating. Here, we tested this hypothesis in a randomised double-blind, placebo-controlled study comparing three different LSD microdoses (5 g, 10g and 20g) with placebo. After capsule administration, participants performed a modified delay-match-to-sample (DMTS) dopamine-sensitive task. The standard DMTS task was modified to include novel items in the delay period between encoding and probe. These novel items either had to be ignored or updated into working memory. There was no evidence that LSD microdoses affected the accuracy or efficiency of working memory recall and there was no evidence for differential effects on ignoring or updating. Due to the small sample of participants, these results are preliminary and larger studies are required to establish whether LSD microdoses affect short-term recall.


title: Mitochondrial control of microglial phagocytosis in Alzheimer's disease

abstract: Microglial phagocytosis is an energetically demanding process that plays a critical role in the removal of toxic aggregates of beta amyloid (A{beta}) in Alzheimers disease (AD). Recent evidence indicates that metabolic programming may breakdown in microglia in AD, thereby disrupting this important protective function. The mechanisms coordinating mitochondrial metabolism to fuel phagocytosis in microglia remain poorly understood, however. Here we demonstrate that mitochondrial displacement of the glucose metabolizing enzyme, hexokinase-II (HK) regulates microglial metabolism and phagocytosis, and that deletion of the translocator protein (TSPO) inhibits this. TSPO is a PET-visible inflammatory biomarker and therapeutic target in AD, previously shown to regulate microglial metabolism via an unknown mechanism. Using RNAseq and proteomic analyses, we found TSPO function in the brain to be linked with the regulation of mitochondrial bioenergetics, lipid metabolism and phagocytosis. In cultured microglia, TSPO deletion was associated with elevated mitochondrial recruitment of HK, which was associated with a switch to non-oxidative glucose metabolism, reduced mitochondrial energy production, lipid storage and impaired phagocytosis. Consistent with in vitro findings, TSPO expression was also associated with phagocytic microglia in both AD brain and AD mice. Conversely, TSPO deletion in AD mice reduced phagocytic microglia and exacerbated amyloid accumulation. Based on these findings we propose that microglial TSPO functions as an immunometabolic brake via regulation of mitochondrial HK recruitment, preventing hyperglycolysis and promoting phagocytosis in AD. Further, we demonstrate that targeting mitochondrial HK may offer a novel immunotherapeutic approach to promote microglial phagocytosis in AD.


title: Sex Differences in Affective States and Association with Voluntary Ethanol Intake in Sprague Dawley Rats

abstract: Alcohol use disorders (AUDs) are a major problem across the United States. While AUD remains a complex human condition, it is difficult to isolate the directionality of anxiety and ethanol (EtOH) drinking from outside influences. The present study sought to investigate the relationship between affective states and EtOH intake using male and female Sprague Dawley rats. Using complementary tests of anxiety- and depressive-like behavior, we found sex- and test-specific differences in basal affective behavior such that females displayed enhanced anxiety-like behavior in the Splash Test and males displayed enhanced anxiety-like behavior in the Novelty Suppressed Feeding Test. Although there were no sex differences in EtOH intake and no correlation between anxiety-like behavior and subsequent EtOH intake, we did find that depressive-like behavior predicted future EtOH intake in females rats only. In addition, we observed an increase in depressive-like behavior is male rats in both the water and EtOH drinking groups. Furthermore, anxiety-like behavior, but not depressive-like behavior predicted subsequent EtOH intake in female rats. Lastly, we found a history of EtOH intake decreased pain thresholds in male and female rats. Together, these experiments provide important information on the complex interaction between negative affect and alcohol intake and how these two contexts reciprocally do, or do not, influence each other in a sex-specific manner.


title: Layer 1 NDNF+ interneurons control bilateral sensory processing in a layer-dependent manner

abstract: Bilateral sensory information is indispensable for navigating the world. In most mammals, signals sensed by either side of the midline will ultimately reach the cortex where they will be integrated for perception and appropriate action selection. Even though information transferred across the hemispheres is routed through the corpus callosum, how and which microcircuits are key in integrating it is not well understood. Here we identify an essential role for layer 1 NDNF+ inhibitory cells of mice in integrating bilateral whisker-evoked information in an NMDA receptor-dependent manner. Direct connections from the contralateral cortex and the ipsilateral side activate NDNF+ neurons, which subsequently inhibit the late spiking activity of underlying layer 2/3 neurons, but not layer 5. Our results identify a feed-forward regulatory pathway for bilateral cortical sensory processing of upper layer cortical neurons actuated via layer 1 NDNF+ interneurons.


title: Relationship between high-frequency activity in the sensory and the motor hand areas, and regional myelin content

abstract:
BackgroundThe human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, transcranial magnetic stimulation (TMS) of M1 can evoke a series of descending volleys in the corticospinal pathway that can be detected non-invasively with a paired-pulse TMS protocol, called short interval intracortical facilitation (SICF). SICF features several peaks of facilitation of motor evoked potentials in contralateral hand muscles, which are separated by inter-peak intervals resembling HFO rhythmicity.

HypothesisIn this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex.

MethodsIn 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out.

ResultsThe individual frequencies and magnitudes of HFO and SICF curves were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r= 0.703, p< 0.001), while their amplitudes were inversely related (r= -0.613, p= 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF.

ConclusionThe results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., as measured with SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human sensorimotor cortex, giving further the opportunity to infer their generators.


title: Relationship between high-frequency activity in the cortical sensory and the motor hand areas, and their regional myelin content


title: Estimating muscle activation from EMG using deep learning-based dynamical systems models

abstract:
ObjectiveTo study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. However, estimating the latent command signal that underlies muscle activation is challenging due to its complex relation with recorded electromyographic (EMG) signals. Common approaches estimate muscle activation independently for each channel or require manual tuning of model hyperparameters to optimally preserve behaviorally-relevant features.

ApproachHere, we adapted AutoLFADS, a large-scale, unsupervised deep learning approach originally designed to de-noise cortical spiking data, to estimate muscle activation from multi-muscle EMG signals. AutoLFADS uses recurrent neural networks (RNNs) to model the spatial and temporal regularities that underlie multi-muscle activation.

Main ResultsWe first tested AutoLFADS on muscle activity from the rat hindlimb during locomotion, and found that it dynamically adjusts its frequency response characteristics across different phases of behavior. The model produced single-trial estimates of muscle activation that improved prediction of joint kinematics as compared to low-pass or Bayesian filtering. We also tested the generality of the approach by applying AutoLFADS to monkey forearm muscle activity from an isometric task. AutoLFADS uncovered previously uncharacterized high-frequency oscillations in the EMG that enhanced the correlation with measured force compared to low-pass or Bayesian filtering. The AutoLFADS-inferred estimates of muscle activation were also more closely correlated with simultaneously-recorded motor cortical activity than other tested approaches.

SignificanceUltimately, this method leverages both dynamical systems modeling and artificial neural networks to provide estimates of muscle activation for multiple muscles that can be used for further studies of multi-muscle coordination and its control by upstream brain areas.


title: Moving Beyond Processing and Analysis-Related Variation in Neuroscience

abstract: When fields lack consensus standards and ground truths for their analytic methods, reproducibility tends to be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools from which scientists can construct processing pipelines and draw interpretations. We provide a critical evaluation of the impact of differences observed in results across five independently developed functional MRI minimal preprocessing pipelines. We show that even when handling the same exact data, inter-pipeline agreement was only moderate, with the specific steps that contribute to the lack of agreement varying across pipeline comparisons. Using a densely sampled test-retest dataset, we show that the limitations imposed by inter-pipeline agreement mainly become appreciable when the reliability of the underlying data is high. We highlight the importance of comparison among analytic tools and parameters, as both widely debated (e.g., global signal regression) and commonly overlooked (e.g., MNI template version) decisions were each found to lead to marked variation. We provide recommendations for incorporating tool-based variability in functional neuroimaging analyses and a supporting infrastructure.


title: LIFELONG CYTOMEGALOVIRUS AND EARLY-LIFE IRRADIATION SYNERGISTICALLY POTENTIATE AGE-RELATED DEFECTS IN RESPONSE TO VACCINATION AND INFECTION

abstract: A popular "DNA-damage theory" of aging posits that unrepaired DNA damage leads to cellular (and organismal) senescence. Indeed, some hallmarks of immune aging are more prevalent in individuals exposed to Whole-Body Irradiation (WBI). To test this hypothesis in a model relevant to human immune aging, we examined separate and joint effects of lifelong latent Murine Cytomegalovirus (MCMV) and early-life WBI (i) over the course of the lifespan; (ii) in response to a West Nile virus (WNV) live attenuated vaccine; and (iii) following lethal WNV challenge subsequent to vaccination. We recently published that a single dose of non-lethal WBI in youth, on its own, was not sufficient to accelerate aging of the murine immune system despite causing widespread DNA damage and repopulation stress in hematopoietic cells. However, 4Gy sub-lethal WBI caused manifest reactivation of MCMV. Following vaccination and challenge with WNV in the old age, MCMV-infected animals experiencing 4Gy, but not lower, dose of sub-lethal WBI in youth had reduced survival. By contrast, old irradiated mice lacking MCMV and MCMV-infected, but not irradiated, mice were both protected to the same high level as the old non-irradiated, uninfected controls. Analysis of the quality and quantity of anti-WNV immunity showed that higher mortality in MCMV-positive WBI mice correlated with increased levels of MCMV-specific immune activation during WNV challenge. Moreover, we demonstrate that infection, including that by WNV, led to MCMV reactivation. Our data suggest that MCMV reactivation may be an important determinant of increased late-life mortality following early-life irradiation and late-life acute infection.


title: Machupo virus with mutations in the transmembrane domain and glycosylation sites is attenuated and immunogenic in animal models of Bolivian Hemorrhagic Fever

abstract:
Several highly pathogenic mammarenaviruses cause severe hemorrhagic and neurologic disease in humans, for which vaccines and antivirals are limited or unavailable. New World (NW) mammarenavirus Machupo virus (MACV) infection causes Bolivian hemorrhagic fever in humans. We previously reported that the disruption of specific N-linked glycan sites on the glycoprotein (GPC) partially attenuate MACV in an IFN-{beta}/{gamma} receptor knockout mouse model. However, some capability to induce neurological pathology still remained. Highly pathogenic Junin virus (JUNV) is another NW arenavirus closely related to MACV. A F427I substitution in the GPC transmembrane domain (TMD) rendered JUNV attenuated in a lethal mouse model after intracranial inoculation. In this study, we rationally designed and rescued a MACV containing mutations at two glycosylation sites and the corresponding F438I substitution in GPC TMD. The MACV mutant is fully attenuated in IFN-{beta}/{gamma} receptor knockout mice and outbred guinea pigs. Furthermore, inoculation with this mutant MACV fully protected guinea pigs from wild-type MACV lethal challenge. Lastly, we found the GPC TMD F438I substitution greatly impaired MACV growth in neuronal cell lines of mouse and human origins. Our results highlight the critical roles of the glycans and the TMD on the GPC in arenavirus virulence, which informs the rational design of potential vaccine candidates for highly pathogenic arenaviruses.

ImportanceFor arenaviruses, the only vaccine available is the live-attenuated Candid#1 vaccine, a JUNV vaccine approved in Argentina. We and others have found that the glycans on GPC and the F427 residue in the GPC TMD are important for virulence of JUNV. Nevertheless, mutating either of them is not sufficient for full and stable attenuation of JUNV. Using reverse genetics, we disrupted specific glycosylation sites on MACV GPC, and also introduced the corresponding F438I substitution in the GPC TMD. This MACV mutant is fully attenuated in two animal models and protects animals from lethal infection. Thus, our studies highlight the feasibility of rational attenuation of highly pathogenic arenaviruses for vaccine development. Another important finding from this study is that the F438I substitution in GPC TMD could substantially affect MACV replication in neurons. Future studies are warranted to elucidate the underlying mechanism and the implication of this mutation in arenavirus neural tropism.


title: Imaging analysis to quantitate the Interplay of membrane and cytoplasm protein dynamics

abstract: Plasma membrane proteins are extremely important in cell signaling and cellular functions. Protein expression and localization alter in response to various signals in a way that is dependent on cell type and niche. Compartmental quantification of the expression of particular proteins is a very useful means of understanding their role in cellular processes. Immunofluorescence staining is frequently used to investigate the distribution of proteins of interest. Here, we present an imaging method for quantifying the membrane to cytoplasm ratio (MCR) of proteins analyzed at single-cell resolution. This technique provides a robust quantification of membrane proteins and contributes new insights into membrane expression dynamics. We have developed a protocol that uses immunostaining to assess protein expression according to the fluorescent cellular distribution and to compute the MCR. The method was applied to measure the MCR of glucose transporter 4 (GLUT4) in response to insulin in 3T3-L1 cells, an in-vitro model for adipocyte function and adipogenesis. The results revealed informative changes in the subcellular localization of GLUT4 following insulin induction. MCR analysis is a powerful imaging tool that can be generally applied to membrane proteins to provide a rapid and efficient quantitative analysis of protein distribution and sub-cellular processes in cells.

category: cell biology


title: From the formation of embryonic appendages to the color of wings: Conserved and novel roles of aristaless1 in butterfly development

abstract: Highly diverse butterfly wing patterns have emerged as a powerful system for understanding the genetic basis of phenotypic variation. While the genetic basis of this pattern variation is being clarified, the precise developmental pathways linking genotype to phenotype are not well understood. The gene aristaless, which plays a role in appendage patterning and extension, has been duplicated in Lepidoptera. One copy, aristaless1, has been shown to control a white/yellow color switch in the butterfly Heliconius cydno, suggesting a novel function associated with color patterning and pigmentation. Here we investigate the developmental basis of al1 in embryos, larvae and pupae using new antibodies, CRISPR/Cas9, RNAi, qPCR assays of downstream targets and pharmacological manipulation of an upstream activator. We find that Al1 is expressed at the distal tips of developing embryonic appendages consistent with its ancestral role. In developing wings, we observe Al1 accumulation within developing scale cells of white H. cydno during early pupation while yellow scale cells exhibit little Al1 at this timepoint. Reduced Al1 expression is also associated with yellow scale development in al1 knockouts and knockdowns. We also find that Al1 expression appears to downregulate the enzyme Cinnabar and other genes that synthesize and transport the yellow pigment, 3-Hydroxykynurenine (3-OHK). Finally, we provide evidence that Al1 activation is under the control of Wnt signaling. We propose a model in which high levels of Al1 during early pupation, which are mediated by Wnt, are important for melanic pigmentation and specifying white portions of the wing while reduced levels of Al1 during early pupation promote upregulation of proteins needed to move and synthesize 3-OHK, promoting yellow pigmentation. In addition, we discuss how the ancestral role of aristaless in appendage extension may be relevant in understanding the cellular mechanism behind color patterning in the context of the heterochrony hypothesis.

category: developmental biology