title: Superior colliculus saccade motor bursts do not dictate movement kinematics

abstract: The primate superior colliculus (SC) contains a topographic map of visual field locations, such that the anatomical location of any given active neuron defines a desired eye movement amplitude and direction. Complementing such a spatial code, SC neurons also exhibit saccade-related bursts that are tightly synchronized with movement onset. Current models suggest that such bursts, and their properties, constitute a temporal rate code that may dictate moment-to-moment movement evolution. However, a recent result demonstrated altered movement properties with minimal changes in SC motor burst strengths (Buonocore, Tian, Khademi, & Hafed, 2021). Here, I support such a dissociation between the SC temporal rate code and instantaneous movement evolution: SC burst strength varies depending on whether saccades are directed towards the upper or lower visual fields, but the movements themselves have similar kinematics. Thus, SC saccade-related motor bursts do not necessarily dictate movement kinematics, motivating investigating other possible functional roles for these bursts.


title: Hexapeptide induces M2 macrophage polarization via the JAK1/STAT6 pathway to promote angiogenesis in bone repair

abstract: Angiogenesis is essential for successful bone defect repair. In normal tissue repair, the physiological inflammatory response is the main regulator of angiogenesis through the activity of macrophages and the cytokines secreted by them. In particular, M2 macrophages which secrete high levels of PDGF-BB are typically considered to promote angiogenesis. A hexapeptide [WKYMVm, (Trp-Lys-Tyr-Met-Val-D-Met-NH2)] has been reported to modulate inflammatory activities. However, the underlying mechanisms by which WKYMVm regulates macrophages remain unclear. In this study, the possible involvement by which WKYMVm induces the polarization of macrophages and affects their behaviors was evaluated. In vitro results showed that macrophages were induced to an M2 rather than M1 phenotype and the M2 phenotype was enhanced by WKYMVm through activation of the JAK1/STAT6 signaling pathway. It was also found that WKYMVm played an important role in the PDGF-BB production increase and proangiogenic abilities in M2 macrophages. Consistent with the results in vitro, the elevated M2/M0 ratio induced by WKYMVm enhanced the formation of new blood vessels in a femoral defect mouse model. In summary, these findings suggest that WKYMVm could be a promising alternative strategy for angiogenesis in bone repair by inducing M2 macrophage polarization.

category: biochemistry


title: Chemical mapping exposes the importance of active site interactions in governing the temperature dependence of enzyme turnover

abstract: Uncovering the role of global protein dynamics in enzyme turnover is needed to fully understand enzyme catalysis. Recently, we have demonstrated that the heat capacity of catalysis, {Delta}CP{ddagger}, can reveal links between the protein free energy landscape, global protein dynamics and enzyme turnover, suggesting that subtle changes molecular interactions at the active site can affect long range protein dynamics and link to enzyme temperature activity. Here we use a model promiscuous enzyme (Glucose dehydrogenase from Sulfolobus Solfataricus) to chemically map how individual substrate interactions affect the temperature dependence of enzyme activity and the network of motions throughout the protein. Utilizing a combination of kinetics, REES spectroscopy and computational simulation we explore the complex relationship between enzyme-substrate interactions and the global dynamics of the protein. We find that changes in {Delta}CP{ddagger} and protein dynamics can be mapped to specific substrate-enzyme interactions. Our study reveals how subtle changes in substrate binding affect global changes in motion and flexibility extending throughout the protein.


title: GraphOmics: an Interactive Platform to Explore and Integrate Multi-Omics Data

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSAn increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for a deeper understanding and insights to be gained from the study. In particular data integration can be performed horizontally, where biological entities from multiple omics measurements are mapped to common reactions and pathways. However, data integration remains a challenge due to the complexity of the data and the difficulty in interpreting analysis results.

ResultsHere we present GraphOmics, a user-friendly platform to explore, integrate multiple omics datasets and support hypothesis generations. Users can upload transcriptomics, proteomics and metabolomics data to GraphOmics. Relevant entities are connected based on their biochemical relationships, and mapped to reactions and pathways from Reactome. From the Data Browser in GraphOmics, mapped entities and pathways can be ranked, sorted and filtered according to their statistical significance (p-values) and fold changes. Context-sensitive panels provide information on the currently selected entities, while interactive heatmaps and clustering functionalities are also available. As a case study, we demonstrated how GraphOmics was used to interactively explore multi-omics data and support hypothesis generations using two complex datasets from existing Zebrafish regeneration and Covid-19 human studies.

ConclusionsGraphOmics is fully open-sourced and freely accessible from https://graphomics.glasgowcompbio.org/. It can be used to integrate multiple omics data horizontally by mapping entities across omics to reactions and pathways. Our demonstration showed that using interactive explorations from GraphOmics, interesting insights and biological hypotheses could be rapidly revealed.

category: bioinformatics


title: Metric Multidimensional Scaling for Large Single-Cell Data Sets using Neural Networks

abstract: Metric multidimensional scaling is one of the classical methods for embedding data into low-dimensional Euclidean space. It creates the low-dimensional embedding by approximately preserving the pairwise distances between the input points. However, current state-of-the-art approaches only scale to a few thousand data points. For larger data sets such as those occurring in single-cell RNA sequencing experiments, the running time becomes prohibitively large and thus alternative methods such as PCA are widely used instead. Here, we propose a neural network based approach for solving the metric multidimensional scaling problem that is orders of magnitude faster than previous state-of-the-art approaches, and hence scales to data sets with up to a few million cells. At the same time, it provides a non-linear mapping between high- and low-dimensional space that can place previously unseen cells in the same embedding.


title: Two evolutionary distinct effectors from a nematode and virus target RanGAP1 and 2 via the WPP domain to promote disease

abstract: The Gpa2 and Rx1 intracellular immune receptors are canonical CC-NB-LRR proteins belonging to the same R gene cluster in potato. Despite sharing high sequence homology, they have evolved to provide defence against unrelated pathogens. Gpa2 detects Gp-RBP-1 effectors secreted by the potato cyst nematode Globodera pallida whereas Rx1 recognizes the viral coat protein (CP) of Potato Virus X (PVX). How Gpa2 and Rx1 perceive their matching effectors remains unknown. Using a combination of in planta Co-Immunoprecipitation and cellular imaging, we show that both Gp-RBP-1 and PVX-CP physically interact with RanGAP2 and RanGAP1 in the cytoplasm of plant cells. Interestingly, this was also demonstrated for the eliciting variants of Gp-RBP-1 and PVX-CP indicating a role for RanGAP1 and RanGAP2 in pathogenicity independent from Gpa2 and Rx1 recognition. Indeed, knocking down both RanGAP homologs reduce cyst nematode and PVX infection. These findings show that RanGAP1/2 act as common host targets of evolutionary distinct effectors from two plant pathogens with different lifestyles. The involvement of RanGAP1/2 to pathogen virulence is a novel role not yet reported for these key host cell components and as such, their possible role in cyst nematode parasitism and viral pathogenicity are discussed. Moreover, from these findings a model emerges for their possible role as co-factor in pathogen recognition by the potato immune receptors Gpa2/Rx1.

category: plant biology


title: AFEchidna is a R package for genetic evaluation of plant and animal breeding datasets

abstract: Progeny tests play important roles in plant and animal breeding programs, and mixed linear models are usually performed to estimate variance components of random effects, estimate the fixed effects (Best Linear Unbiased Estimates, BLUEs) and predict the random effects (Best Linear Unbiased Predictions, BLUPs) via restricted maximum likehood (REML) methods in progeny test datasets. The current pioneer software for genetic assessment is ASReml, but it is commercial and expensive. Although there is free software such as Echidna or the R package sommer, the Echidna syntax is complex and the R package functionality is limited. Therefore, this study aims to develop an R package named AFEchidna based on Echidna software. The mixed linear models are conveniently implemented for users through the AFEchidna package to solve variance components, genetic parameters and the BLUP values of random effects, and the batch analysis of multiple traits, multiple variance structures and multiple genetic parameters can be also performed, as well as comparison between different models and genomic BLUP analysis. The AFEchidna package is free, please email us (yzhlinscau@163.com) to get a copy if reader is interested for it. The AFEchidna package is developed to expand free genetic assessment software with the expectation that its efficiency could be close to the commercial software.


title: Ectosomes and exosomes are distinct proteomic entities that modulate spontaneous activity in neuronal cells

abstract: Extracellular vesicles (EVs) are important mediators in intercellular communication. However, understanding the biological origin and functional effects of EVs subtypes has been challenging due to the moderate differences in their physical properties and absence of reliable markers. Here, we characterize the proteomes of ectosomes and exosomes using an improved differential ultracentrifugation protocol and quantitative proteomics. Cytoskeleton and glycolytic proteins are distinctively present in ectosomes, while endosomal sorting complexes proteins and tetraspanins are enriched in exosomes. Furthermore, annexin-A2 was identified as a specific marker for ectosomes derived from cell media and human cerebrospinal fluid. Expression of EGFP as a cytosolic reporter leads to its incorporation in EVs and enables their imaging with higher resolution. Importantly, ectosomes and exosomes internalization in neuronal cells results in the modulation of neuronal spontaneous activity. Our findings suggest that EVs cargoes reflect core intracellular processes, and their functional properties might regulate basic biological and pathological processes.

category: neuroscience


title: Inter- and intrapopulational heterogeneity of characteristic markers in adult human neural crest-derived stem cells

abstract: Adult human neural crest-derived stem cells (NCSCs) are found in a variety of adult tissues and show an extraordinary broad developmental potential. NCSCs are therefore promising candidates for applications in regenerative medicine, although increasing evidence suggest a remaining niche-dependent variability between different NCSC-populations regarding their behavior and expression signatures. In the present study, we extended the view on heterogeneity of NCSCs by identifying heterogeneous expression levels and protein amounts of characteristic markers even between NCSCs from the same niche of origin. In particular, populations of neural crest-derived inferior turbinate stem cells (ITSCs) isolated from different individuals showed significant variations in characteristic NCSC marker proteins Nestin, S100 and Slug in a donor-dependent manner. Notably, increased nuclear protein amounts of Slug were accompanied by a significantly elevated level of nuclear NF-{kappa}B-p65 protein, suggesting an NF-{kappa}B-dependent regulation of NCSC-makers. In addition to this interpopulational genetic heterogeneity of ITSC-populations from different donors, single ITSCs also revealed a strong heterogeneity regarding the protein amounts of Nestin, S100, Slug and NF-{kappa}B-p65 even within the same clonal culture. Our present findings therefor strongly suggest ITSC-heterogeneity to be at least partly based on an interpopulational genetic heterogeneity dependent on the donor accompanied by a stochastic intrapopulational heterogeneity between single cells. We propose this stochastic intrapopulational heterogeneity to occur in addition to the already described genetic variability between clonal NCSC-cultures and the niche-dependent plasticity of NCSCs. Our observations offer a novel perspective on NCSC-heterogeneity, which may build the basis to understand heterogeneous NCSC-behavior and improve their clinical applicability.

category: cell biology


title: Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates

abstract: Malformations of or injuries to the developing lung are associated with perinatal morbidity and mortality with lifelong consequences for subsequent pulmonary health. One fetal exposure linked with poor health outcomes is chorioamnionitis, which impacts up to 25-40% of preterm births. Severe chorioamnionitis with prematurity is associated with significantly increased risk of pulmonary disease and secondary infections in childhood, suggesting that fetal inflammation may significantly alter developmental ontogeny of the lung. To test this hypothesis, we used intra-amniotic lipopolysaccharide (LPS, endotoxin) to generate experimental chorioamnionitis in prenatal Rhesus macaque (Macaca mulatta), a model which shares critical structural and temporal aspects of human lung development. Inflammatory injury directly disrupts the developing gas exchange surface of the primate lung, with extensive damage to alveolar structure, particularly the close association and coordinated differentiation of alveolar type 1 pneumocytes and specialized alveolar capillary endothelium. Single cell RNA sequencing analysis defined a multicellular alveolar signaling niche driving alveologenesis which was extensively disrupted by perinatal inflammation, leading to loss of gas exchange surface and alveolar simplification similar to that found in chronic lung disease of newborns. Blockade of IL1{beta} and TNF ameliorated endotoxin-induced inflammatory lung injury by blunting stromal response to inflammation and modulating innate immune activation in myeloid cells, restoring structural integrity and key signaling networks in the developing alveolus. These data provide new insight into the pathophysiology of developmental lung injury and suggest that modulating inflammation is a promising therapeutic approach to prevent fetal consequences of chorioamnionitis.

category: developmental biology


title: Environment Classification for Robotic Leg Prostheses and Exoskeletons using Deep Convolutional Neural Networks

abstract: Robotic leg prostheses and exoskeletons can provide powered locomotor assistance to older adults and/or persons with physical disabilities. However, the current locomotion mode recognition systems being developed for intelligent high-level control and decision-making use mechanical, inertial, and/or neuromuscular data, which inherently have limited prediction horizons (i.e., analogous to walking blindfolded). Inspired by the human vision-locomotor control system, we designed and evaluated an advanced environment classification system that uses computer vision and deep learning to forward predict the oncoming walking environments prior to physical interaction, therein allowing for more accurate and robust locomotion mode transitions. In this study, we first reviewed the development of the ExoNet database - the largest and most diverse open-source dataset of wearable camera images of indoor and outdoor real-world walking environments, which were annotated using a hierarchical labelling architecture. We then trained and tested over a dozen state-of-the-art deep convolutional neural networks (CNNs) on the ExoNet database for large-scale image classification of the walking environments, including: EfficientNetB0, InceptionV3, MobileNet, MobileNetV2, VGG16, VGG19, Xception, ResNet50, ResNet101, ResNet152, DenseNet121, DenseNet169, and DenseNet201. Lastly, we quantitatively compared the benchmarked CNN architectures and their environment classification predictions using an operational metric called NetScore, which balances the image classification accuracy with the computational and memory storage requirements (i.e., important for onboard real-time inference). Although we designed this environment classification system to support the development of next-generation environment-adaptive locomotor control systems for robotic prostheses and exoskeletons, applications could extend to humanoids, autonomous legged robots, powered wheelchairs, and assistive devices for persons with visual impairments.

category: bioengineering


title: A Robust and Scalable Graph Neural Network for Accurate Single Cell Classification

abstract:
MotivationSingle-cell RNA sequencing (scRNA-seq) techniques provide high-resolution data on cellular heterogeneity in diverse tissues, and a critical step for the data analysis is cell type identification. Traditional methods usually cluster the cells and manually identify cell clusters through marker genes, which is time-consuming and subjective. With the launch of several large-scale single-cell projects, millions of sequenced cells have been annotated and it is promising to transfer labels from the annotated datasets to newly generated datasets. One powerful way for the transferring is to learn cell relations through the graph neural network (GNN), while vanilla GNN is difficult to process millions of cells due to the expensive costs of the message-passing procedure at each training epoch.

ResultsHere, we have developed a robust and scalable GNN-based method for accurate single cell classification (GraphCS), where the graph is constructed to connect similar cells within and between labelled and unlabelled scRNA-seq datasets for propagation of shared information. To overcome the slow information propagation of GNN at each training epoch, the diffused information is pre-calculated via the approximate Generalized PageRank algorithm, enabling sublinear complexity for a high speed and scalability on millions of cells. Compared with existing methods, GraphCS demonstrates better performance on simulated, cross-platform, and cross-species scRNA-seq datasets. More importantly, our model can achieve superior performance on a large dataset with one million cells within 50 minutes.


title: Jointly learning T-cell receptor and transcriptomic information to decipher the immune response

abstract: T cells play a pivotal role in the adaptive immune system recognizing foreign antigens through their T-cell receptor (TCR). Although the specificity and affinity of the TCR to its cognate antigen determines the functionality, the phenotypic differentiation and thereby also the fate of the T cell remain poorly understood. Therefore, studying the transcriptional changes of T cells in the context of their TCRs is key to deeper insights into T-cell biology. To this end, we developed a multiview Variational Autoencoder (mvTCR) to jointly embed transcriptomic and TCR sequence information at a single-cell level to better capture the phenotypic behavior of T cells. We evaluated mvTCR on two datasets showing a clear separation of the cell state and their functionality, thus, providing a more biologically informative representation than models using each modality individually.


title: The Clade Displacement Index: how to detect hotizontal gene transfers in unrooted gene trees

abstract:
While most genes of any organism are inherited vertically - i.e. from its parent organisms - sometimes they can be exchanged between unrelated species in a process known as the horizontal gene transfer (HGT). Studies of HGT contribute to our knowledge about the mechanisms of evolution, including the emergence of new pathogens, and a great deal of effort has been put into different methods of finding transferred genes. The golden standard of HGT detection is the analysis of the incongruence between the gene and the species trees. Those methods typically require rooted trees, in which the direction of evolution is known. Gene trees are typically unrooted, and rooting them is yet another step in HGT analysis, prone to errors which may lead to wrong conclusions. A natural question arises: can HGTs be detected in gene trees without rooting them at all?

It turns out that, for a particular, yet broad, class of transfers, the answer to this question is: yes. It also turns out that the same methodology can be applied to complement the bootstrap support in assessing the stability of gene tree topology. In this article, we present the Clade Displacement Index, a measure of shift of a given clades location between two trees. We derive algorithms to compute it and give several examples of its applications to HGT detection and gene tree stability analysis. We finish by pointing out directions for further studies and an example that shows that not all HGTs are detectable without knowing the location of the root of the gene tree.

A Jupyter Notebook with the implementation and applications of CDI described in this paper is available at https://github.com/mciach/CDI


title: The Clade Displacement Index: how to detect horizontal gene transfers in unrooted gene trees


title: Effects of trypsin on aggregation, disaggregation and aggregate morphology of red blood cells in autologous plasma and serum

abstract: We study the influence of trypsin on aggregation, disaggregation, and aggregate morphology of RBCs in autologous plasma and serum. The effect of trypsin on the surface charge of red blood cells and the aggregation of glutaraldehyde fixed cells after treatment with the enzyme was also studied. RBC aggregation was studied by means of an aggregometer and microscopic observations. The results obtained in this study indicate that trypsin treatment increases RBCs aggregation in autologous plasma and serum. The disaggregation of erythrocytes after trypsin treatment considerably decreased in autologous plasma and serum. Increase in the strength of red blood cell aggregates was observed in autologous plasma and serum. The microscopic images of RBCs aggregates indicate the formation of globular (pathologic) structures of aggregates in autologous plasma and serum. Trypsin decrease the surface charge of RBCs. In autologous plasma and serum, the cup shapes of RBCs appear. The control RBCs fixed with glutaraldehyde were not aggregated after their placement in autologous plasma. At the same time, red blood cells pretreated with trypsin and fixed with glutaraldehyde interact with each other in autologous plasma. The physiological significance of glycoproteins of erythrocyte surface for RBCs aggregation was discussed.

category: biophysics


title: Reproducing Human Motor Adaptation in Spiking Neural Simulation and known Synaptic Learning Rules

abstract:
Sensorimotor adaptation enables us to adjust our goal-oriented movements in response to external perturbations. These phenomena have been studied experimentally and computationally at the level of human and animals reaching movements, and have clear links to the cerebellum as evidenced by cerebellar lesions and neurodegeneration. Yet, despite our macroscopic understanding of the high-level computational mechanisms it is unclear how these are mapped and are implemented in the neural substrates of the cerebellum at a cellular-computational level. We present here a novel spiking neural circuit model of the sensorimotor system including a cerebellum which control physiological muscle models to reproduce behaviour experiments. Our cerebellar model is composed of spiking neuron populations reflecting cells in the cerebellar cortex and deep cerebellar nuclei, which generate motor correction to change behaviour in response to perturbations. The model proposes two learning mechanisms for adaptation: predictive learning and memory formation, which are implemented with synaptic updating rules. Our model is tested in a force-field sensorimotor adaptation task and successfully reproduce several phenomena arising from human adaptation, including well-known learning curves, aftereffects, savings and other multi-rate learning effects. This reveals the capability of our model to learn from perturbations and generate motor corrections while providing a bottom-up view for the neural basis of adaptation. Thus, it also shows the potential to predict how patients with specific types of cerebellar damage will perform in behavioural experiments. We explore this by in silico experiments where we selectively incapacitate selected cerebellar circuits of the model which generate and reproduce defined motor learning deficits.

Author summaryA rich body of work in human motor neuroscience developed high-level computational theories of sensorimotor control, learning and adaptation. But there is a gap in understanding how this may be implemented and learn on the level of neurons, synapses and spikes. Conversely, studies of patients with cerebellar lesions or neurological disease highlight the essential role the cerebellum plays in our ability to perform motor learning. Yet, how these anatomical and molecular defects play out in terms of human movement have to date not been linked to a model that spans multiple level of biological organisation from neural circuits to reproducing human motor experiments. To address this gap, we present a spiking neuron of the sensorimotor system focused on the cerebellum, with which we can on the one side reproduce the high-level behaviour learning phenomena observed in healthy subjects, as well as quantitatively predicting the putative effects on human movement trajectories of cerebellar lesions implemented at the cellular level.


title: A convolutional neural network for the quality control of MRI defacing

abstract: Large-scale neuroimaging datasets present unique challenges for automated processing pipelines. Mo-tivated by a large clinical trials dataset of Multiple Sclerosis with over 235,000 MRI scans, we consider the challenge of defacing - anonymisation to remove identifying facial features. The defacing process must undergo quality control (QC) checks to ensure that the facial features have been adequately anonymised and that the brain tissue is left completely intact. Visual QC checks - particularly on a project of this scale - are time-consuming and can cause delays in preparing data. We have developed a convolutional neural network (CNN) that can assist with the QC of the application of MRI defacing; our CNN is able to distinguish between scans that are correctly defaced, and can also classify defacing failures into three sub-types to facilitate parameter tuning during remedial re-defacing. Since integrating the CNN into our anonymisation pipeline, over 75,000 scans have been processed. Strict thresholds have been applied so that ambiguous classifications are referred for visual QC checks, however all scans still undergo a time-efficient verification check before being marked as passed. After applying the thresholds, our network is 92% accurate and is able to classify nearly half of the scans without the need for protracted manual checks. Even with the introduction of the verification checks, incorporation of the CNN has reduced the time spent undertaking QC checks by 42% during initial defacing, and by 35% overall. With the help of the CNN, we have been able to successfully deface 96% of the scans in the project whilst maintaining high QC standards. In a similarly sized new project of this scale, we would expect the model to reduce the time spent on manual QC checks by 125 hours. Our approach is applicable to other projects with the potential to greatly improve the efficiency of imaging anonymisation pipelines.


title: Application of a convolutional neural network to the quality control of MRI defacing


title: Chilean blind spots in soil biodiversity and ecosystem function research

abstract: Soil harbor up to a quarter of the worlds biodiversity, contributing to many ecosystem functions. It is of great importance to identify distribution patterns of soil organisms and their ecosystem functions to support their conservation and policy building. This has been recently analyzed at macroecological scales, but analyses at national/local scales are scarce. Here we identify and analyze the blind spots in soil taxa and ecosystem functioning data in continental Chile, through a Web of Science articles (1945-2020) search, and focusing on ten soil taxonomic groups and four ecosystem functions (nutrient cycling, decomposition, water infiltration, soil respiration). A total of 741 sampling sites were obtained from 239 articles. In 49.25% of the sites soil biodiversity was studied, while this percentage was 32.65% for ecosystem functions; in 18.10% of the sites both soil biodiversity and ecosystem functions were investigated at the same time, a surprisingly high percentage compared to global studies. By far, Bacteria/Fungi and nutrient cycling were the most investigated taxa and function, respectively. There is a significant number of soil taxa (Acari, Collembola, Nematoda, Formicoidea, Protista, Rotifera) represented by just a few sites concentrated in specific Chilean regions. Places like the central regions, the Atacama desert, and the Valdivian temperate forests present a proliferation of studies on soil Fungi, Bacteria, and nutrient cycling, reflecting historical interests of established research groups. Based on this research, we are identifying the causes of the data blind spots and invite the Chilean soil ecology community to propose ideas on how to fill them.

category: ecology


title: Directed Evolution of AAV Targeting Primate Retina by Intravitreal Injection Identifies R100, a Variant Demonstrating Robust Gene Delivery and Therapeutic Efficacy in Non-Human Primates

abstract: Targeted AAV vectors are needed for safe and efficient delivery to and transduction of specific tissue target(s) in patients. Effective intravitreal delivery for retina gene therapy is not feasible with wildtype AAV. We employed directed evolution in nonhuman primates (NHP) to discover an AAV variant (R100) for intravitreal treatment of multiple target cells in the primate retina. R100 demonstrated superior transduction of human retinal cells compared to wildtype AAV. Furthermore, three R100-based gene therapeutics demonstrated safety, delivery, and durable pan-retinal expression of intracellular or secreted transgenes throughout the NHP retina following intravitreal administration. Finally, efficacy of R100-mediated delivery of therapeutic transgenes was demonstrated in patient-derived retinal cells (monogenic diseases) and in an NHP model of pathogenic retinal angiogenesis.


title: Probing Neuro-Endocrine Interactions Through Wireless Magnetothermal Stimulation of Peripheral Organs

abstract: Exposure to stress alters hypothalamic-pituitary-adrenal (HPA) axis reactivity; however, it is unclear exactly how or where within the HPA pathway these changes occur. Dissecting these mechanisms requires tools to reliably probe HPA function, particularly the adrenal component, with temporal precision. We previously demonstrated magnetic nanoparticle (MNP) technology to remotely trigger adrenal hormone release by activating thermally sensitive ion channels. Here, we applied adrenal magnetothermal stimulation to probe stress-induced HPA axis changes. MNP and control nanoparticles were injected into the adrenal glands of outbred rats subjected to a tone-shock conditioning/extinction/recall paradigm. We measured MNP-triggered adrenal release before and after conditioning through physiologic (heart rate) and serum (epinephrine, corticosterone) markers. Aversive conditioning altered adrenal function, reducing corticosterone and blunting heart rate increases post-conditioning. MNP-based organ stimulation provides a novel approach to probing the function of HPA and other neuro-endocrine axes and could help elucidate changes across stress and disease models.


title: Design and validation of a multi-point injection technology for MR-guided convection enhanced delivery in the brain

abstract: Convection enhanced delivery (CED) allows direct intracranial administration of neuro-therapeutics. Success of CED relies on specific targeting and broad volume distributions (VD). However, to prevent off-target delivery and tissue damage, CED is typically conducted with small cannulas and at low flow rates, which critically limit the maximum achievable VD. Furthermore, in applications such as gene therapy requiring injections of large fluid volumes into broad subcortical regions, low flow rates translate into long infusion times and multiple surgical trajectories. The cannula design is a major limiting factor in achieving broad VD, while minimizing infusion time and backflow. Here we present and validate a novel multi-point cannula specifically designed to optimize distribution and delivery time in MR-guided intracranial CED of gene-based therapeutics. First, we evaluated the compatibility of our cannula with MRI and common viral vectors for gene therapy. Then, we conducted CED tests in agarose brain phantoms and benchmarked the results against single-needle delivery. 3T MRI in brain phantoms revealed minimal susceptibility-induced artifacts, comparable to the device dimensions. Benchtop CED of adeno-associated virus demonstrated no viral loss or inactivation. CED in agarose brain phantoms at 3, 6, and 9 L/min showed >3x increase in volume distribution and 60% time reduction compared to single-needle delivery. This study confirms the validity of a multi-point delivery approach for improving infusate distribution at clinically-compatible timescales and supports the feasibility of our novel cannula design for advancing safety and efficacy of MR-guided CED to the central nervous system.


title: The Forget-Me-Not dHCP study: 7 Tesla high resolution diffusion imaging in the unfixed post-mortem neonatal brain

abstract: Diffusion MRI of the neonatal brain allows investigation of the organisational structure of maturing fibres during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. The Forget-Me-Not study, part of the Developing Human Connectome Project (dHCP), aims to acquire and publicly distribute high-resolution diffusion MRI data for unfixed post-mortem neonatal brain at 7T with a custom-built head coil. This paper describes how the study addressed logistical, technical and ethical challenges relating to recruitment pipeline, care pathway, tissue preservation, scan setup and protocol optimisation. Results from the first subject recruited to the study demonstrate high-quality diffusion MRI data. Preliminary voxel-wise and tractography-based analyses are presented for the cortical plate, subplate and white matter pathways, with comparison to age-matched in vivo dHCP data. These results demonstrate that high quality post-mortem data can be acquired and provide a sensitive means to explore the developing human brain, as well as altered diffusion properties consistent with post-mortem changes, at high resolution.


title: Transformation and Preprocessing of Single-Cell RNA-Seq Data

abstract:
The count table, a numeric matrix of genes x cells, is the basic input data structure in the analysis of single-cell RNA-seq data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so that the variance is similar across the dynamic range. These steps are intended to make subsequent application of generic statistical methods more palatable. Here, we describe three transformations (based on the delta method, model residuals, or inferred latent expression state) and compare their strengths and weaknesses. We find that although the residuals and latent expression state-based models have appealing theoretical properties, in benchmarks using simulated and real-world data the simple shifted logarithm in combination with principal component analysis performs surprisingly well.

SoftwareAn R package implementing the delta method and residuals-based variance-stabilizing transformations is available on github.com/const-ae/transformGamPoi.

Contactconstantin.ahlmann@embl.de


title: Nanoparticle-mediated transgene expression of insulin-like growth factor 1 in the guinea pig placenta differentially affects fetal liver gene expression depending on maternal nutrient status

abstract:
Fetal growth restriction (FGR) occurs in up to 10% of pregnancies and is a leading cause of infant morbidity and mortality. Additionally, FGR has been implicated in contributing to the development of long-term health outcomes including increasing the risk for future cardiovascular and endocrine diseases. Currently, there is limited preventative strategies and no effective treatment options for FGR. To address this need, we are developing a therapeutic targeting the placenta to increase expression of human insulin-like growth factor 1 (hIGF-1) and enhance placental development and function, with the goal of correcting fetal growth trajectories.

MethodsInitially, an ultrasound-guided, transcutaneous, intra-placental injection of a non-viral, Texas-red conjugated polymer-based nanoparticle containing a plasmid with the green fluorescent protein (GFP) gene under the control of the placenta-specific promotors Plac1 or Cyp19a1 was performed to determine nanoparticle uptake and transgene expression in the guinea pig placenta. Subsequently, using the established maternal nutrient restriction (MNR) guinea pig model of FGR, placentas were treated with an unconjugated nanoparticle containing a plasmid with the hIGF-1 gene under the Cyp19a1 promotor at mid-pregnancy (gestational day (GD) 30-33). Five days after treatment placentas and fetal liver tissue was collected, weighed, and fixed for histology or snap-frozen for qPCR analysis of mRNA expression.

ResultsHistological analysis of Texas-red and GFP fluorescence in placenta and fetal liver tissue confirmed nanoparticle uptake and transgene expression and that nanoparticle was unable to cross the placenta to fetal circulation. In situ hybridization for plasmid-specific mRNA confirmed sustained hIGF-1 expression five days after treatment. MNR resulted in 20-25% decreased fetal weight at mid-pregnancy (P<0.001) that was not changed with nanoparticle treatment (P>0.05). There was no effect of nanoparticle treatment on the volume densities of trophoblasts or fetal capillaries in the placenta (P>0.05 for both). However, treatment did reduce the interhaemal distance between the maternal blood space and fetal circulation in the MNR placentas compared to sham treated MNR placentas (P<0.001). In the fetuses, placental nanoparticle treatment increased circulating glucose by 38-50% (P<0.001) and was associated with differential changes to fetal liver mRNA expression of genes associated with gluconeogenesis. Gene expression changes were dependent on if the fetus was growth restricted or not; nanoparticle treatment: down-regulated gluconeogenesis gene expression in the normal growing fetuses but increased expression in the FGR fetuses.

ConclusionsThe current study shows that treatment of the guinea pig placenta with a polymer-based nanoparticle causes expression of hIGF-1 and ultimately increases fetal glucose concentrations within five days of treatment. Furthermore, the data shows that the placenta and fetal liver respond differently to nanoparticle treatment depending on fetal growth conditions.

Graphical Abstract

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category: physiology


title: The PLETHORA/PIN-FORMED/AUXIN network mediates terminal prehaustorium formation in the parasitic plant Striga hermonthica

abstract: The parasitic plant Striga hermonthica invades the host root through the formation of a haustorium and has detrimental impacts on cereal crops. The haustorium is derived directly from the differentiation of the Striga radicle. Currently, how Striga root cell lineages are patterned and the molecular mechanisms leading to radicle differentiation shortly after germination remain unclear. In this study, we determined the developmental-morphodynamic programs that regulate terminal haustorium formation in S. hermonthica at spatiotemporal and cellular resolutions. We showed that in S. hermonthica roots, meristematic cells first undergo multiplanar divisions, which decrease during growth and correlate with reduced expression of the stem cell regulator PLETHORA1. We also found that PIN-FORMED (PIN) proteins undergo a shift in polarity. Using the layout of the root structure and the polarity of outer-membrane PIN proteins, we constructed a mathematical model of auxin transport that explains the auxin distribution patterns observed during S. hermonthica root growth. Our results reveal a fundamental molecular and cellular framework governing the switch of S. hermonthica roots from the vegetative to the invasive state by inducing meristem differentiation through auxin excretion to the environment and explain how asymmetric PIN polarity controls auxin distribution to maintain meristem activity and sustain root growth.


title: Short-term dynamics of long-range corticocortical synapses revealed by selective optical stimulation

abstract: Short-term plasticity regulates the strength of central synapses as a function of previous activity. In the neocortex, direct synaptic interactions between areas play a central role in cognitive function, but the activity-dependent regulation of these long-range corticocortical connections and their impact on a postsynaptic target neuron is unclear. Here, we use an optogenetic strategy to study the connections between mouse primary somatosensory and motor cortex. We found that short-term facilitation was strong in both corticocortical synapses, resulting in far more sustained responses than local intra-cortical and thalamocortical connections. A major difference between pathways was that the synaptic strength and magnitude of facilitation were distinct for individual excitatory cells located across all cortical layers and specific subtypes of GABAergic neurons. Facilitation was dependent on the presynaptic calcium sensor synaptotagmin-7 and altered by several optogenetic approaches. Current-clamp recordings revealed that during repetitive activation, the short-term dynamics of corticocortical synapses enhanced the excitability of layer 2/3 pyramidal neurons, increasing the probability of spiking with activity. Furthermore, the properties of the connections linking primary with secondary somatosensory cortex resemble those between somatosensory-motor areas. These short-term changes in transmission properties suggest long-range corticocortical synapses are specialized for conveying information over relatively extended periods.


title: Short-term facilitation of long-range corticocortical synapses revealed by selective optical stimulation


title: High affinity FcγR activating function depends on IRAP+ endosomal-signaling platforms

abstract:
Although endocytosis of cell surface receptors is generally thought to terminate the signaling, for some receptors, endocytosis sustains signaling. We wondered if endosomal signaling participates to the function of the receptors for Fc immunoglobulin fragments (FcRs) that are highly internalized after their activation. We demonstrate here that four different FcRs follow distinct endocytic pathways after activation. While FcRI is internalized into lysosomes, Fc{gamma}RIIA is internalized and partially retained in early endosomes, whereas the inhibitory receptor Fc{gamma}RIIB is internalized in endosomes decorated by the autophagy marker LC3. Interestingly, the high affinity Fc{gamma}RI is internalized in specialized endosomal compartments described by the Insulin Responsive AminoPeptidase (IRAP), where it remains associated with the active form of the signaling kinase Syk. Our results show that Fc{gamma}RI has the ability to build endosomal-signaling platforms, which depend on the presence of IRAP and Rab14. Destabilization of the endosomal signaling platforms compromised the ability of peritoneal macrophages to kill tumor cells by antibody-dependent cell mediated cytotoxicity, indicating that Fc{gamma}RI endosomal signaling is required for the therapeutic action of anti-tumor monoclonal antibodies.

One sentence summaryBinding of immune complexes to Fc{gamma}RI receptor leads to receptor internalization and sustained signaling from endosomes described by the Insulin Responsive AminoPeptidase and the small GTPase Rab14.

category: immunology


title: Evidence of multiple origins of glyphosate resistance evolution in Lolium multiflorum

abstract:
O_LIThe multitude of herbicide resistance patterns in the weed Lolium multiflorum L. is a remarkable example of the rapid adaptation to anthropogenic-driven disturbance. Recently, resistance to glyphosate was identified in multiple populations of L. multiflorum in Oregon.
C_LIO_LIWe used phenotypic approaches, as well as population genomic and gene expression analyses, to determine if known mechanisms were responsible for glyphosate resistance, if resistance phenotypes evolved independently in different populations, and to identify potential loci contributing to resistance.
C_LIO_LIWe found no evidence of genetic alterations or expression changes at known target and non-target sites of glyphosate resistance. Population genomic analyses indicated that resistant populations tended to have largely distinct ancestry from one another, with little evidence of admixture, suggesting that glyphosate resistance did not spread among populations via gene flow. Rather, resistance appears to have evolved independently on different genetic backgrounds. We also detected potential loci associated with the resistance phenotype, some of which encode proteins with potential effects on herbicide metabolism.
C_LIO_LIOur results suggest that Oregon populations of L. multiflorum evolved resistance to glyphosate due to a novel mechanism. Future studies that characterize the gene or genes involved in resistance will be necessary to confirm this conclusion.
C_LI

category: evolutionary biology


title: Elucidating the genome of Emydura subglobosa through manual annotation and computational biology tools

abstract: Rapid advancements in automated genomic technologies have uncovered many unique findings about the turtle genome and its associated features including olfactory gene expansions and duplications of toll-like receptors. However, automated technologies often result in a high frequency of errors through the process of assembly and annotation and highlight the need for manual annotation. In this study, we have manually annotated four genes of the red-bellied short-neck turtle (Emydura subglobosa), an understudied outgroup of turtles representing a diverse lineage. We improved upon initial ab initio gene predictions through homology-based evidence and generated refined consensus models. Through functional, localization, and structural analyses of the predicted proteins, we have discovered conserved genes encoding proteins that play a role in C21-steroid hormone biosynthetic processes, Vitamin A uptake, collagen/elastin integrity, tumor suppression, and fatty acid catabolism. Overall, these findings further our knowledge about the genetic features underlying turtle physiology, morphology, and longevity, which could have important implications for the treatment of human diseases and evolutionary studies.

category: genomics


title: A novel flight style allowing the smallest featherwing beetles to excel

abstract: Flight speed generally correlates positively with animal body size1. Surprisingly, miniature featherwing beetles can fly at speeds and accelerations of insects three times as large2. We show here that this performance results from a previously unknown type of wing motion. Our experiment combines three-dimensional reconstructions of morphology and kinematics in one of the smallest insects, Paratuposa placentis (body length 395 m). The flapping bristled wing follows a pronounced figure-eight loop that consists of subperpendicular up and down strokes followed by claps at stroke reversals, above and below the body. Computational analyses suggest a functional decomposition of the flapping cycle in two power half strokes producing a large upward force and two down-dragging recovery half strokes. In contrast to heavier membranous wings, the motion of bristled wings of the same size requires little inertial power. Muscle mechanical power requirements thus remain positive throughout the wing beat cycle, making elastic energy storage obsolete. This novel flight style evolved during miniaturization may compensate for costs associated with air viscosity and helps explain how extremely small insects preserved superb aerial performance during miniaturization. Incorporating this flight style in artificial flappers is a challenge for designers of micro aerial vehicles.

category: zoology


title: Distinct Hippocampal Neuronal Reactions Reveal Different Neuronal Codes for Memory Generalization

abstract: To survive in an ever-changing world we need to learn and memorize associations of environmental stimuli and generalize them to new situations. Both memory and generalization critically rely on the hippocampus, but it is unclear how hippocampal neuronal activities represent memory and generalization, and if a conserved hippocampal mechanism serves these functions. Here we compared neuronal activities in hippocampal CA1 region of two sub-strains of the widely used C57BL/6 mice, C57BL/6J (B6J) and C57BL/6NCrl (B6NCrl), in contextual fear conditioning. Both sub-strains learnt well but differed in freezing and generalization. They displayed distinct early-late bi-phasic reactions to the unconditioned stimulus. While in both sub-strains the neurons showing late-phase reactions were preferentially engaged in memory representation, the neuronal activity feature that correlated with generalization level differed in the two sub-strains: in B6NCrl, these neurons activity level during learning negatively correlated with the generalization level; in B6J, functional coupling of these late-phase neurons with other neurons positively correlated with the generalization level. We further found that the distinct neuronal reactions were accompanied by distinct GABAb receptor-mediated inhibition but not by differences in the major synaptic inputs or neuronal excitability of the CA1. Therefore, this comparative study reveals two signature neuronal activity features in learning that can predict generalization levels. The results also demonstrate that differences in hippocampal network properties lead to diverse hippocampal mechanisms in memory encoding and generalization.


title: Macrosystem community assembly patterns are predicted by foundation tree species genetic connectivity and environment across the American Southwest

abstract: Macrosystems ecology is an emerging science that aims to integrate traditionally distinct disciplines to predict how hierarchical interacting processes influence the emergence of complex patterns across local to regional and global scales. Despite increased focus on cross-scale relationships and cross-disciplinary integration, few macroecology studies incorporate genetic-based processes. Here we used a community genetics approach to investigate the pattern-process relationships underlying the emergence of macroscale biodiversity patterns. We tested the hypothesis that environmental variation, geography, and genetic connectivity in a foundation tree species differentially predict associated community assembly patterns from local to continental scales. Using genome-wide SNP data, we assessed genetic connectivity as a function of genetic similarity and structure in Fremont cottonwood (Populus fremontii) across its distribution throughout the southwestern US and Mexico. For the same trees, we measured community composition, diversity, and abundance of leaf modifying arthropods and sequenced targeted amplicons of twig fungal endophytes. Five key findings emerged. (1) We identified three primary and six secondary population genetic groups within P. fremontii, which occupy distinct climate niches. (2) Both the leaf modifying arthropod and fungal endophyte communities were significantly differentiated across host tree ecotypes, with genetic distance among sampling locations explaining 13-17% of respective macroscale community structure. (3) For arthropods, environmental distance was the strongest driver of community similarity. (4) Conversely, host genetic connectivity was the most important contributor to macroscale endophyte community structure, with no significant contribution of environmental distance. (5) Furthermore, we observed a shift in the strength of interspecific relationships, with host genetics most strongly influencing associated communities at the intermediate population scale. Our findings suggest that genetic connectivity and environmental variation play integrated roles in macroscale community assembly, and their relative importance changes with scale. Thus, conservation genetic management of the diversity harbored within foundation species is vital for sustaining associated regional biodiversity.


title: Genetic evidence for environment-dependent hybrid incompatibilities in threespine stickleback

abstract: Hybrid incompatibilities occur when interactions between opposite-ancestry alleles at different loci reduce the fitness of hybrids. Most work on incompatibilities has focused on those that are  intrinsic, meaning they affect viability and sterility in the laboratory. Theory predicts that ecological selection can also underlie hybrid incompatibilities, but tests of this hypothesis are scarce. In this article, we compiled genetic data for F2 hybrid crosses between divergent populations of threespine stickleback fish (Gasterosteus aculeatus L.) that were born and raised in either the field (semi-natural experimental ponds) or the laboratory (aquaria). We tested for differences in excess heterozygosity between these two environments at ancestry informative loci--a genetic signature of selection against incompatibilities. We found that excess ancestry heterozygosity was elevated by approximately 3% in crosses raised in ponds compared to those raised in aquaria. Previous results from F1 hybrids in the field suggest that pond-specific (single-locus) heterosis is unlikely to explain this finding. Our study suggests that, in stickleback, a coarse signal of environment-dependent hybrid incompatibilities is reliably detectable and that extrinsic incompatibilities have evolved before intrinsic incompatibilities.


title: Non-Newtonian Patient-specific Simulations of Left Atrial Hemodynamics

abstract: The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects can be subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered in calculating patient-specific blood stasis indices by computational fluid dynamics.


title: Non-Newtonian Blood Rheology Impacts Left Atrial Stasis in Patient-Specific Simulations


title: WMW-A: Rank-based two-sample independent test for small sample sizes through an auxiliary sample

abstract: Two-sample independent test methods are widely used in case-control studies to identify significant changes or differences, for example, to identify key pathogenic genes by comparing the gene expression levels in normal and disease cells. However, due to the high cost of data collection or labelling, many studies face the small sample problem, for which the traditional two-sample test methods often lose power. We propose a novel rank-based nonparametric test method WMW-A for small sample problem by introducing a three-sample statistic through another auxiliary sample. By combining the case, control and auxiliary samples together, we construct a three-sample WMW-A statistic based on the gap between the average ranks of the case and control samples in the combined samples. By assuming that the auxiliary sample follows a mixed distribution of the case and control populations, we analyze the theoretical properties of the WMW-A statistic and approximate the theoretical power. The extensive simulation experiments and real applications on microarray gene expression data sets show the WMW-A test could significantly improve the test power for two-sample problem with small sample sizes, by either available unlabelled auxiliary data or generated auxiliary data.


title: Protection of the prodomain 1-helix correlates with latency in the transforming growth factor- family

abstract: The 33 members of the transforming growth factor beta (TGF-{beta}) family are fundamentally important for organismal development and homeostasis. Family members are synthesized and secreted as pro-complexes of prodomains that are non-covalently bound to the growth factor (GF). The pro-complexes of some members are latent and require activation steps to release the GF for signaling. Why some members are latent while others are non-latent is incompletely understood, but crystal structures and hydrogen-deuterium exchange (HDX) of four family members have begun to unravel how latency is regulated. Here, we extend this understanding by comparing pro-complex conformation in negative stain EM (nsEM) and HDX of ActA, BMP7, BMP9, BMP10, GDF8, TGF-{beta}1, and TGF-{beta}2. nsEM revealed that family members varied in either adopting cross-armed, open-armed, or V-armed configurations. Latency was achieved in both cross-armed and V-armed but not open-armed conformations. HDX revealed remarkably varying patterns of exchange between family members, consistent with large prodomain sequence divergence. We observed a strong correlation between latency and protection of the prodomain 1-helix from exchange, which in latent members coincided with greater buried surface area of the 1-helix and more hydrogen and cation-pi bonds from the prodomain fastener and GF to the 1-helix. Strong sequence conservation of the 1-helix and fastener only in latent members suggests that similar interactions are conserved and sufficient to confer latency. Moreover, most members exhibited rapid exchange in the unstructured "association region" at the prodomain N-terminus, highlighting their availability for interacting with factors that may regulate latency and extracellular storage.


title: MELD-DNA: A new tool for capturing protein-DNA binding

abstract: Herein we present MELD-DNA, a novel computational approach to address the problem of protein-DNA structure prediction. This method addresses well-known issues hampering current computational approaches to bridge the gap between structural and sequence knowledge, such as large conformational changes in DNA and highly charged electrostatic interaction during binding. MELD-DNA is able to: i) sample multiple binding modes, ii) identify the preferred binding mode from the ensembles, and iii) provide qualitative binding preferences between DNA sequences. We expect the results presented herein will have impact in the field of biophysics (through new software development), structural biology (by complementing DNA structural databases) and supramolecular chemistry (by bringing new insights into protein-DNA interactions).


title: Identification and characterization of novel proteins from Arizona bark scorpion venom that inhibit Nav1.8, a voltage-gated sodium channel regulator of pain signaling

abstract: The voltage-gated sodium channel Nav1.8 is linked to neuropathic and inflammatory pain, highlighting the potential to serve as a drug target. However, the biophysical mechanisms that regulate Nav1.8 activation and inactivation gating are not completely understood. Progress has been hindered by a lack of biochemical tools for examining Nav1.8 gating mechanisms. Arizona bark scorpion (Centruroides sculpturatus) venom proteins inhibit Nav1.8 and block pain in grasshopper mice (Onychomys torridus). These proteins provide tools for examining Nav1.8 structure-activity relationships. To identify proteins that inhibit Nav1.8 activity, venom samples were fractioned using liquid chromatography (reversed phase and ion exchange). A recombinant Nav1.8 clone expressed in ND7/23 cells was used to identify subfractions that inhibited Nav1.8 Na+ current. Mass spectrometry-based bottom-up proteomic analyses identified unique peptides from inhibitory subfractions. A search of the peptides against the AZ bark scorpion venom gland transcriptome revealed four novel proteins between 40 and 60% conserved with venom proteins from scorpions in four genera (Centruroides, Parabuthus, Androctonus, and Tityus). Ranging from 63 to 82 amino acids, each primary structure includes 8 cysteines and a "CXCE" motif where X = an aromatic residue (tryptophan, tyrosine or phenylalanine). Electrophysiology data demonstrated that the inhibitory effects of bioactive subfractions can be removed by hyperpolarizing the channels, suggesting that proteins may function as gating modifiers as opposed to pore blockers.

category: pharmacology and toxicology


title: Unprecedented incidence of Trypanosoma cruzi infections in a cohort of dogs directly detected through longitudinal tracking at multi-dog kennels, Texas, USA

abstract: Canine Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is increasingly recognized as a health concern for dogs in the USA, and infected dogs may signal geographic regions of risk for human disease. Dogs living in multi-dog kennel environments where triatomine vectors are endemic may be at high risk for infection. We monitored a cohort of 64 T. cruzi-infected and uninfected dogs from across 10 kennels in Texas, USA, to characterize changes in infection status over time. We used robust diagnostic criteria in which reactivity on multiple independent platforms was required to be considered positive. Among the 30 dogs enrolled as serologically- and/or PCR-positive, all but one dog showed sustained positive T. cruzi diagnostic results over time. Among the 34 dogs enrolled as serologically- and PCR-negative, 10 new T. cruzi infections were recorded over a 12-month period. The resulting incidence rate was 30.7 T. cruzi infections per 100 dogs per year. This study highlights the risk of T. cruzi infection to dogs in kennel environments, despite multiple vector control methods employed by kennel owners. To protect both dog and human health, there is an urgent need to develop more integrated vector control methods as well as prophylactic and curative antiparasitic treatment options for T. cruzi infection in dogs.


title: Oiling the gears of memory: quercetin exposure during memory formation, consolidation, and recall enhances memory in Lymnaea stagnalis

abstract:
Memory formation (short-term, intermediate-term, and long-term) is an integral process of cognition which allows individuals to retain important information and is influenced by various intrinsic and extrinsic factors. A major extrinsic factor influencing cognition across taxa is diet, which may contain rich sources of molecular agents with antioxidant, anti-inflammatory, and memory enhancing properties that potentially enhance cognitive ability. A common and abundant flavonoid present in numerous food substances is quercetin (Q) which is also known to upregulate cyclic AMP response element binding protein (CREB) in several animals including our model system Lymnaea stagnalis. Since CREB is known to be involved in long term memory (LTM) formation, we investigated the role of Q-exposure on memory formation, consolidation, and recall during operant conditioning of aerial respiratory behaviour in Lymnaea. Snails were exposed to Q 3h before or after training to ascertain its effects on LTM. Additionally, we investigated the effect of the combined presentation of a single reinforcing stimulus (at 24h post-training or 24h before training) and Q-exposure on both LTM formation and reconsolidation. Our data indicate that Q-exposure acts on the different phases of memory formation, consolidation, and recall leading to enhanced LTM formation.

Summary StatementQuercetin enhances long-term memory formation acting on the different phases of memory formation, consolidation, and recall.


title: Sensory and choice responses in MT distinct from motion encoding

abstract: Macaque area MT is well known for its visual motion selectivity and relevance to motion perception, but the possibility of it also reflecting non-sensory functions has largely been ignored. Manipulating subjects temporal evidence weighting revealed multiple components of MT responses that were, surprisingly, not interpretable as behaviorally-relevant modulations of motion encoding, nor as consequences of readout of motion direction. MTs time-varying motion-driven responses were starkly changed by our strategic manipulation, but with timecourses opposite the subjects temporal weighting strategies. Furthermore, large choice-correlated signals were represented in population activity distinctly from motion responses (even after the stimulus) with multiple phases that both lagged psychophysical readout and preceded motor responses. These results reveal multiple cognitive contributions to MT responses that are task-related but not functionally relevant to encoding or decoding of motion for psychophysical direction discrimination, calling into question its nature as a simple sensory area.


title: New Drosophila models to uncover the intrinsic and extrinsic factors mediating the toxicity of the human prion protein

abstract: Misfolded conformations of the prion protein (PrP) are responsible for devastating neurological disorders in humans and mammals. An unresolved problem is unraveling the mechanisms governing PrP conformational dynamics, misfolding, and the cellular mechanism leading to neurodegeneration. The variable susceptibility of mammals to prion diseases can be exploited to understand the conformational dynamics of PrP. Here we present a new fly model expressing human PrP with robust phenotypes in brain neurons and the eye. Using comparable attP2 insertions, we demonstrate the heightened toxicity of human PrP compared to that of mouse and hamster PrP along with a specific interaction with the amyloid-beta peptide. Using this new highly toxic new model, we started to uncover the intrinsic (sequence / structure) and extrinsic (interactions) factors regulating PrP toxicity. As extrinsic factors, we describe the importance of the PERK - ATF4 branch of the unfolded protein response as a key cellular mechanism mediating the toxicity of human PrP. For intrinsic factors, we introduced point mutations in human PrP (N159D, D167S, N174S) that were partially protective, revealing its high propensity to misfold into toxic conformations.


title: The NLRP3/eIF2 axis drives cell cycle progression in acute myeloid leukemia

abstract:
Aberrant activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome mediates numerous inflammatory diseases. Oncogenes can activate the NLRP3 inflammasome and thereby promote myeloproliferative neoplasia, suggesting a crucial role of NLRP3 in the malignant transformation of hematopoietic cells. Here, we show that bone marrow-derived mononuclear cells of AML patients display enhanced expression of NLRP3, IL-1{beta} and IL-18 and that high-level expression of NLRP3 is linked to poor survival of AML patients. Pharmacological and genetic inhibition of NLRP3 inflammasome activation attenuated cell proliferation of MOLM-13 AML cells in vitro. In vivo, genetic inhibition of NLRP3 in MOLM-13 AML cells resulted in reduced engraftment potential in xenografts, along with reduced splenomegaly and organ infiltration. Differential proteomic analysis revealed the eIF2 pathway as potential target of NLRP3 in AML, with a significant increase of eIF2 phosphorylation upon NLRP3 inhibition. NLRP3 inhibition also caused a strong decrease in cyclin - dependent kinases CDK4 and CDK6, accompanied by an upregulation of the CDK inhibitor p21 (CDKN1A) and a marked arrest of cell cycle progression in the G0/G1 phase, consistent with the role of eIF2 phosphorylation as negative cell cycle regulator.

Taken together, we show that inhibition of the NLRP3 inflammasome reduces AML cell proliferation by promoting eIF2 phosphorylation, which in turn enhances the expression of cell cycle arrest genes such as p21. Thus, the study uncovers the NLRP3/eIF2 axis as new driver of AML proliferation and proposes a novel therapeutic treatment of AML by targeted inhibition of NLRP3 activation.


title: Macrophage metabolism in the intestine is compartment-specific and regulated by the microbiota

abstract: Intestinal macrophages play a vital role in the maintenance of gut homeostasis through signals derived from the microbiota. We previously demonstrated that microbial-derived metabolites can shape the metabolic functions of macrophages. Here, we show that antibiotic-induced disruption of the intestinal microbiota dramatically alters both the local metabolite environment, and the metabolic functions of macrophages in the colon. Broad-spectrum antibiotic administration in mice increased expression of the large neutral amino acid transporter and accordingly, amino acid uptake. Subsequently, antibiotic administration enhanced the metabolic functions of colonic macrophages, increasing phosphorylation of components of mammalian/mechanistic target of rapamycin (mTOR) signalling pathways, increasing expression of genes involved in glycolysis and oxidative phosphorylation (OXPHOS), increasing mitochondrial function and increased levels of ECAR and OCR as a direct measure of glycolysis and OXPHOS. Small bowel macrophages were less metabolically active than in the colon, with macrophage metabolism being independent of the microbiota. Finally, we reveal tissue resident Tim4+ CD4+ macrophages exhibit enhanced fatty acid uptake alongside reduced fatty acid synthesis compared to their recruited counterparts. Thus the microbiota shapes gut macrophage metabolism in a compartment-specific manner, with important implications for functions when monocyte recruitment and macrophage differentiation.


title: c-di-GMP inhibits early sporulation in Clostridioides difficile

abstract:
The formation of dormant spores is essential for the anaerobic pathogen Clostridioides difficile to survive outside of the host gastrointestinal tract. The regulatory pathways and environmental signals that initiate C. difficile spore formation within the host are not well understood. One bacterial second messenger signaling molecule, cyclic diguanylate (c-di-GMP), modulates several physiological processes important for C. difficile pathogenesis and colonization, but the impact of c-di-GMP on sporulation is unknown. In this study, we investigated the contribution of c-di-GMP to C. difficile sporulation. Overexpression of a gene encoding a diguanylate cyclase, dccA, decreased sporulation frequency and early sporulation gene transcription in both the epidemic R20291 and historical 630{Delta}erm strains. Expression of a dccA allele encoding a catalytically inactive DccA that is unable to synthesize c-di-GMP no longer inhibited sporulation, indicating that the accumulation of intracellular c-di-GMP reduces C. difficile sporulation. A null mutation in dccA slightly increased sporulation in R20291 and slightly decreased sporulation in 630{Delta}erm, suggesting that DccA may contribute to the intracellular pool of c-di-GMP in a strain-dependent manner. However, these data were highly variable, underscoring the complex regulation involved in modulating intracellular c-di-GMP concentrations. Finally, overexpression of dccA in known sporulation mutants revealed that c-di-GMP is likely signaling through an unidentified regulatory pathway to control early sporulation events in C. difficile. C-di-GMP-dependent regulation of C. difficile sporulation may represent an unexplored avenue of potential environmental and intracellular signaling that contributes to the complex regulation of sporulation initiation.

IMPORTANCEMany bacterial organisms utilize the small signaling molecule cyclic diguanylate (c-di-GMP) to regulate important physiological processes, including motility, toxin production, biofilm formation, and colonization. C-di-GMP inhibits motility and toxin production and promotes biofilm formation and colonization in the anaerobic, gastrointestinal pathogen Clostridioides difficile. However, the impact of c-di-GMP on C. difficile spore formation, a critical step in this pathogens life cycle, is unknown. Here, we demonstrate that c-di-GMP negatively impacts sporulation in two clinically relevant C. difficile strains, the epidemic R20291 and the historical 630{Delta}erm. The pathway through which c-di-GMP controls sporulation was investigated, and our results suggest that c-di-GMP is likely signaling through an unidentified regulatory pathway to control C. difficile sporulation. This work implicates c-di-GMP metabolism as a potential mechanism to integrate environmental and intracellular cues through c-di-GMP levels to influence C. difficile sporulation.

category: microbiology


title: mOTUpan: a robust Bayesian approach to leverage metagenome assembled genomes for core-genome estimation

abstract: Recent advances in sequencing and bioinformatics have expanded the tree of life by providing genomes for uncultured environmentally relevant clades, either through metagenome assembled genomes (MAGs) or single-cell assembled genomes (SAGs). While this expanded diversity can provide novel insights about microbial population structure, most tools available for core-genome estimation are overly sensitive to genome completeness. Consequently a major portion of the huge phylogenetic diversity uncovered by environmental genomics approaches remain excluded from such analyses. We present mOTUpan, a novel iterative Bayesian method for computing the core-genome for sets of genomes of highly diverse completeness range. The likelihood for each gene-cluster to belong to core- or accessory-genome is estimated by computing the probability of its presence/absence pattern in the target set of genomes. The core-genome prediction is computationally efficient and can be scaled up to thousands of genomes. It has shown comparable estimates as state-of-the-art tools Roary and PPanGGoLiN for high-quality genomes and outperforms them at lower completeness thresholds. mOTUpan wraps a bootstrapping procedure to estimate the quality of a specific core-genome prediction, as the accuracy of each run will depend on the specific completeness distribution and the number of genomes in the dataset under scrutiny. mOTUpan is implemented in the mOTUlizer software package, and available at github.com/moritzbuck/mOTUlizer, under GPL 3.0 license.


title: BayesDeBulk: A Flexible Bayesian Algorithm for the Deconvolution of Bulk Tumor Data

abstract: Characterizing the tumor microenvironment is crucial in order to improve responsiveness to immunotherapy and develop new therapeutic strategies. The fraction of different cell-types in the tumor microenvironment can be estimated based on transcriptomic profiling of bulk tumor data via deconvolution algorithms. One class of such algorithms, known as reference-based, rely on a reference signature containing gene expression data for various cell-types. The limitation of these methods is that such a signature is derived from the gene expression of pure cell-types, which might not be consistent with the transcriptomic profiling in solid tumors. On the other hand, reference-free methods usually require only a set of cell-specific markers to perform deconvolution; however, once the different components have been estimated from the data, their labeling can be problematic. To overcome these limitations, we propose BayesDeBulk - a new reference-free Bayesian method for bulk deconvolution based on gene expression data. Given a list of markers expressed in each cell-type (cell-specific markers), a repulsive prior is placed on the mean of gene expression in different cell-types to ensure that cell-specific markers are upregulated in a particular component. Contrary to existing reference-free methods, the labeling of different components is decided a priori through a repulsive prior. Furthermore, the advantage over reference-based algorithms is that the cell fractions as well as the gene expression of different cells are estimated from the data, simultaneously. Given its flexibility, BayesDeBulk can be utilized to perform bulk deconvolution beyond transcriptomic data, based on other data types such as proteomic profiles or the integration of both transcriptomic and proteomic profiles.


title: The Personalized Cancer Network Explorer (PeCaX) as a visual analytics tool to support molecular tumor boards

abstract:
BackgroundPersonalized oncology represents a shift in cancer treatment from conventional methods to target specific therapies where the decisions are made based on the patient specific tumor profile. Selection of the optimal therapy relies on a complex interdisciplinary analysis and interpretation of these variants by experts in molecular tumor boards. With up to hundreds of somatic variants identified in a tumor, this process requires visual analytics tools to guide and accelerate the annotation process.

ResultsThe Personal Cancer Network Explorer (PeCaX) is a visual analytics tool supporting the efficient annotation, navigation, and interpretation of somatic genomic variants through functional annotation, drug target annotation, and visual interpretation within the context of biological networks. Starting with somatic variants in a VCF file, PeCaX enables users to explore these variants through a web-based graphical user interface. The most protruding feature of PeCaX is the combination of clinical variant annotation and gene-drug networks with an interactive visualization. This reduces the time and effort the user needs to invest to get to a treatment suggestion and helps to generate new hypotheses. PeCaX is being provided as a platform-independent containerized software package for local or institution-wide deployment. PeCaX is available for download at https://github.com/KohlbacherLab/PeCaX-docker.


title: Annealing synchronizes the 70S ribosome into a minimum-energy conformation

abstract:
Researchers commonly anneal metals, alloys, and semiconductors to repair defects and improve microstructures via recrystallization. Theoretical studies indicate simulated annealing on biological macromolecules helps predict the final structures with minimum free energy. Experimental validation of this homogenizing effect and further exploration of its applications are fascinating scientific questions that remain elusive. Here, we chose the apo-state 70S ribosome from Escherichia coli as a model, wherein the 30S subunit undergoes a thermally driven inter-subunit rotation and exhibits substantial structural flexibility as well as distinct free energy. We experimentally demonstrate that annealing at a fast cooling rate enhances the 70S ribosome homogeneity and improves local resolution on the 30S subunit. After annealing, the 70S ribosome is in a nonrotated state with respect to corresponding intermediate structures in unannealed or heated ribosomes, and exhibits a minimum energy in the free energy landscape. One can readily crystallize these minimum-energy ribosomes, which have great potential for synchronizing proteins on a single-molecule level. Our experimental results are consistent with theoretical analysis on the temperature-dependent Boltzmann distribution, and offer a facile yet robust approach to enhance protein stability, which is ideal for high-resolution cryogenic electron microscopy. Beyond structure determination, annealing can be extended to study protein folding and explore conformational and energy landscape.

Significance statementIn metallurgy, annealing heats a metal or alloy to a predetermined temperature, holding for a certain time, and then cooling to room temperature to change the physical and sometimes also the chemical properties of the material. Researchers introduce the similar concept as simulated annealing to predict minimum-energy conformations of biological macromolecules. In this work, we experimentally verify that annealing at a fast cooling rate can synchronize the 70S ribosome into a nonrotated state with a minimum energy in the free energy landscape. Our results not only offer a facile yet robust approach to stabilize proteins for high-resolution structural analysis, but also contribute to the understanding of protein folding and temperature adaptation.


title: Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat

abstract: Understanding the genetic basis of agronomic traits is essential for wheat breeding programmes to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can become a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin that were phenotyped for agronomic and VI traits derived from multispectral images over three and two years, respectively. GWAS identified 2579 marker-trait associations (MTAs). The QTL overview index statistic detected 11 QTL hotspots involving more than one trait in at least two years. A candidate gene analysis detected 12 CGs upregulated under abiotic stress in 6 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.


title: Genome-wide identification and characterization of DNA/RNA differences associated with Fusarium graminearum infection in wheat

abstract: RNA editing (DNA/RNA differences) as a post-transcriptional modification approach to enrich genetic information, plays the crucial role in regulating diverse biological processes in eukaryotes. Although it has been extensively studied in plant chloroplast and mitochondria genome, RNA editing in plant nuclear genome, especially those associated with Fusarium head blight (FHB), is not well studied at present. Here, we investigated the DNA/RNA differences associated with FHB through a novel method by comparing the RNA-seq data from Fusarium-infected and control samples from 4 wheat genotypes. A total of 187 DNA/RNA differences were identified in 36 wheat genes, representing the first landscape of the FHB-responsive RNA editome in wheat. Furthermore, all of these 36 edited genes were located in the FHB related co-expression gene modules, which may involve in regulating FHB response. Finally, the effects of DNA/RNA differences were systematically investigated to show that they could cause the change of RNA structure and protein structure in edited genes. In particular, the G to C editing (chr3A_487854715) in TraesCS3A02G263900, which is the orthology of OsRACK1, resulted that it was targeted by tae-miR9664-3p to control its expression in different genotype through different editing efficiency, suggesting RNA editing could mediate miRNA to participate in the regulation network of FHB tolerance. This study reported the first wheat DNA/RNA differences associated with FHB, which not only contribute to better understand the molecular basis underlying FHB tolerance, but also shed light on improving FHB tolerance through epigenetic method in wheat and beyond.


title: Intramolecular 13C/12C signals inform about carbon allocation in plant leaves

abstract:
Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at treering glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesising leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference of leaf-cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

HighlightIntramolecular 13C/12C analysis resolves information about carbon uptake and allocation (and associated environmental controls) enabling more comprehensive assessments of carbon metabolism, plant-environment interactions, and environmental variability than whole-molecule 13C/12C analysis.


title: Intramolecular 13C signals inform about carbon allocation in plants


title: Intramolecular carbon isotope signals reflect metabolite allocation in plants


title: Methods for in situ quantitative root biology

abstract: When dealing with plant roots, a multi-scale description of the functional root structure is needed. Since the beginning of XXI century, new devices like laser confocal microscopes have been accessible for coarse root structure measurements, including 3D reconstruction. Most researchers are familiar with using simple 2D geometry visualization that does not allow quantitatively determination of key morphological features from an organ-like perspective. We provide here a detailed description of the quantitative methods available for three-dimensional (3D) analysis of root features at single cell resolution, including root asymmetry, lateral root analysis, xylem and phloem structure, cell cycle kinetics, and chromatin determination. Quantitative maps of the distal and proximal root meristems are shown for different species, including Arabidopsis thaliana, Nicotiana tabacum and Medicago sativa. A 3D analysis of the primary root tip showed divergence in chromatin organization and cell volume distribution between cell types and precisely mapped root zonation for each cell file. Detailed protocols are also provided. Possible pitfalls in the usage of the marker lines are discussed. Therefore, researchers who need to improve their quantitative root biology portfolio can use them as a reference.


title: Genomic miscellany and allelic frequencies of Plasmodium falciparum msp-1, msp-2 and glurp in parasite isolates

abstract:
The genomic miscellany of malaria parasites can inform the intensity of transmission and identify potential deficiencies in malaria control programs. The aim of this study was to investigate the genomic miscellany, allele frequencies and multiplicity of infection (MOI) of P. falciparum.

MethodsA total of 85 isolates from patients presenting to the local health centers with P. falciparum species were collected from 2017 to 2019. Parasite DNA was extracted from a total of 200 {micro}l whole blood per patient using the Qiagen DNA extraction kit according to manufactures instructions. The polymorphic region of msp-1, msp-2 and glurp loci were genotyped by using nested polymerase chain reactions followed by gel electrophoresis for fragment analysis.

ResultsGenetic diversity and allelic frequencies of msp-1, msp-2 and glurp were identified in 85 blood samples. A total of 62 msp alleles were detected in which 30 for msp-1 and 32 for msp-2. For msp-1 the successful amplification occurred in (75/85) 88.23% isolates for msp-1, 78.9% (67/85) for msp-2 and 70% (60/85) for glurp. For msp-1, the K1 allelic family was predominant at 66.66% (50/75), followed by RO33 and MAD20. The frequency of samples having only K1, MAD20 and RO33 were 21.34% (16/75), 8% (6/75) and 10.67% (8/75) respectively. In msp-2, the FC27 allelic family was the most abundant with 70.14% (47/67) compared to 3D7 with 67.16% (45/67). Nine glurp RII region genotypes were identified. The overall mean multiplicity of infection was 2.6 with1.8 and 1.4 for msp-1 and msp-2 respectively while for glurp RII genes (MOI=1.03). There was no significant association between multiplicity of infection and age group (Spearmans rank coefficient = 0.050; P = 0.6). There was significant correlation between MOI and parasite density for msp-2 allelic family.

ConclusionOur study showed high genetic diversity and allelic frequency with multiple clones of msp-1, msp-2 and glurp in P. falciparum isolates from malaria patients in Khyber Pakhtunkhwa Pakistan. In the present study the genotype data provided the valuable information which is essential for monitoring the impact of malaria eradication efforts in this region.


title: The contribution of the European LIFE program to mitigate damages caused by large carnivores in Europe

abstract:
Governments around the world invest considerable resources to reduce damages caused by large carnivores on human property. To use these investments more efficiently and effectively, we need to understand which interventions successfully prevent such damages and which do not. In the European Union, the LIFE program represents by far the largest financial instrument to help EU Member States with the implementation of conservation activities, including mitigation of damages caused by large carnivores. However, we currently lack information about the effectiveness of this funding program in reducing carnivore damages. We reviewed 135 LIFE projects dealing with large carnivores between 1992 and 2019 to provide an overview of the use of damage prevention methods and evaluate their functional and perceived effectiveness. Methods evaluated ranged from non-lethal and lethal interventions, to information dissemination and compensation schemes. The largest number of the projects was focused on grey wolf (Canis lupus) and brown bears (Ursus arctos) in the Mediterranean countries and in Romania. Electric fences were reported as the most successful method for reducing damages by large carnivores, and most of the non-lethal methods used showed at least moderate effectiveness. However, standards of measuring and reporting effectiveness were in general relatively low, which limits our ability to measure actual impact. Therefore we urge project managers and evaluators to improve these standards, as well as the dissemination of the project results. We provide a list of recommendations for improving measuring and reporting success of implemented interventions for the benefit of future projects aimed to reduce damages caused by wildlife.

Article impact statementElectric fences were reported as the most effective method to prevent large-carnivore damages and are recommended for future use.


title: Clusters of neuronal Neurofascin prefigure node of Ranvier position along single axons

abstract: The spacing of nodes of Ranvier crucially affects conduction properties along myelinated axons. It has been assumed that node position is primarily driven by the growth of myelin sheaths. Here, we reveal an additional mechanism of node positioning that is driven by the axon. We show through longitudinal live imaging of node formation dynamics that stable clusters of the cell adhesion molecule Neurofascin A accumulate at specific sites along axons prior to myelination. While some of these clusters change position upon encounter with growing myelin sheaths, others restrict sheath extension and are therefore predictive of future node position. Animals that lack full-length Neurofascin A showed increased internodal distances and less regular spacing of nodes along single axons. Together, our data reveal the existence of an axonal mechanism to position its nodes of Ranvier that does not depend on regulation of myelin sheath length.


title: Efficient prestimulus network integration of FFA biases face perception during binocular rivalry

abstract: Ongoing fluctuations in neural excitability and connectivity influence whether or not a stimulus is seen. Do they also influence which stimulus is seen? We recorded magnetoencepahlography data while participants viewed face or house stimuli, either one at a time or under bi-stable conditions induced through binocular rivalry. Multivariate pattern analysis revealed common neural substrates for rivalrous vs. non-rivalrous stimuli with an additional delay of ~36ms for the bi-stable stimulus and poststimulus signals were source-localized to the fusiform face area (FFA). Prior to stimulus onset followed by a face-vs. house-report, FFA showed stronger connectivity to primary visual cortex and to the rest of the cortex in the alpha frequency range (8-13 Hz) but there were no differences in local oscillatory alpha power. The pre-stimulus connectivity metrics predicted the accuracy of post-stimulus decoding and the delay associated with rivalry disambiguation suggesting that perceptual content is shaped by ongoing neural network states.


title: Flexible encoding of objects and space in single cells of the dentate gyrus

abstract: The hippocampus is involved in the formation of memories that require associations among stimuli to construct representations of space and the items and events within that space. Neurons in the dentate gyrus (DG), an initial input region of the hippocampus, have robust spatial tuning, but it is unclear how nonspatial information may be integrated with spatially modulated firing at this stage. We recorded from the DG of 21 adult mice as they foraged for food in an environment that contained discrete objects. By classifying recorded DG cells into putative granule cells and mossy cells, we examined how the addition or displacement of objects affected the spatial firing of these DG cell types. We found DG cells with multiple firing fields at a fixed distance and direction from objects (landmark vector cells) as well as cells that exhibited localized changes in spatial firing when objects in the environment were manipulated. When mice were exposed to a second environment with the same objects, DG spatial maps were completely reorganized, suggesting standard global remapping, and a largely different subset of cells responded to object manipulations. Together, these data reveal the capacity of DG cells to detect small changes in the environment, while preserving a stable spatial representation of the overall context.