Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment Studying the visual system with fMRI often requires using localizer paradigms to define regions of interest (ROIs). However, the considerable interindividual variability of the cerebral cortex represents a crucial confound for group-level analyses. Cortex-based alignment (CBA) techniques reliably reduce interindividual macroanatomical variability. Yet, their utility has not been assessed for visual field localizer paradigms, which map specific parts of the visual field within retinotopically organized visual areas. We evaluated CBA for an attention-enhanced visual field localizer mapping homologous parts of each visual quadrant in 50 participants. We compared CBA with volume-based alignment and a surface-based analysis, which did not include macroanatomical alignment. CBA led to the strongest increase in the probability of activation overlap (up to 40 percent). On the group level, CBA led to the most consistent increase in ROI size while preserving vertical ROI symmetry. Overall, our results indicate, that in addition to the increased signal-to-noise ratio of a surface-based analysis macroanatomical alignment considerably improves statistical power. These findings confirm and extend the utility of CBA for the study of the visual system in the context of group analyses. CBA should be particularly relevant when studying neuropsychiatric disorders with abnormally increased interindividual macroanatomical variability.
Rostral Anterior Cingulate Activations inversely relate to Reward Payoff Maximation & predict Depressed Mood Choice selection strategies and decision making are typically investigated using multiple-choice gambling paradigms that require participants to maximize reward payoff. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains to choose smaller local gains over larger longer term gain, also referred to as melioration. Here, we developed a simple two-choice reward task, implemented in 186 healthy human adult subjects across the adult lifespan to understand the behavioral, computational, and neural bases of payoff maximization versus melioration. The observed reward choice behavior on this task was best explained by a reinforcement learning model of differential future reward prediction. Simultaneously recorded and source-localized electroencephalography (EEG) showed that diminished theta-band activations in the right rostral anterior cingulate cortex (rACC) correspond to greater reward payoff maximization, specifically during the presentation of cumulative reward information at the end of each task trial. Notably, these activations (greater rACC theta) predicted depressed mood symptoms, thereby showcasing a reward processing marker of potential clinical utility.

Significance StatementThis study presents cognitive, computational and neural (EEG-based) analyses of a rapid reward-based decision-making task. The research has the following three highlights. 1) It teases apart two core aspects of reward processing, i.e. long term expected value maximization versus immediate gain frequency melioration based choice behavior. 2) It models reinforcement learning based behavioral differences between individuals showing that observed performance is best explained by differential extents of reward prediction. 3) It investigates neural correlates in 186 healthy human subjects across the adult lifespan, revealing specific theta band cortical source activations in right rostral anterior cingulate as correlates for maximization that further predict depressed mood across subjects.
Multi-omic analysis of the Arabidopsis clock activator mutant rve 4 6 8 reveals connections to carbohydrate metabolism and proteasome regulation Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE proteins (RVEs) are recently discovered members of the plant circadian circuitry that activate the evening complex and PRR genes to maintain regular circadian oscillation. The RVE 8 protein and its two homologs, RVE 4 and 6, have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw novel connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset, provides substantial new insights into the far reaching impact RVE8-like proteins have on the diel plant cell environment. Computational and experimental studies of the breathing motion of a protein loop: implications in PfAMA1-PfRON2 late-stage binding event Protein-protein interactions are important targets for various drug discovery campaigns. One such promising and therapeutically pertinent protein-protein complex is PfAMA1-PfRON2 involved in malarial parasite invasion into human red blood cells. A thorough understanding of the interactions between these macromolecular binding partners is crucial for designing better therapeutics against this age-old disease. Although crystal structures of several PfAMA1-PfRON2 complexes are available, the mechanism of how domain II loop associates with PfRON2 is not clear. The current work investigates how the domain II loop of PfAMA1 exerts its effect on the alpha helix of the PfRON2, thus influencing the overall kinetics of this intricate recognition phenomenon. To this end, we have computationally simulated the dynamics and free energetics of domain II loop closing processes and identified a set of key amino acid residues of PfRON2 helix which are essential for binding. The subsequent evaluation of the binding affinity of Ala-substituted PfRON2 peptide ligands by surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC) validates the relative importance of the residues in context. Together, the combination of computational and experimental investigation reveals that the domain II loop of PfAMA1 is in fact responsible for arresting the PfRON2 molecule from egress, K2027 and D2028 of PfRON2 being the determinant residues for the capturing event. Our study provides a comprehensive understanding of the molecular recognition event between PfAMA1 and PfRON2, specifically in the post binding stage, which could potentially open up new avenues to drug discovery against malaria.

TOC GRAPHIC

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/463826v2_ufig1.gif" ALT="Figure 1">
View larger version (35K):
org.highwire.dtl.DTLVardef@1c26022org.highwire.dtl.DTLVardef@356357org.highwire.dtl.DTLVardef@10ceb04org.highwire.dtl.DTLVardef@1195633_HPS_FORMAT_FIGEXP  M_FIG C_FIG Impact of circadian time of dosing on cardiomyocyte-autonomous effects of glucocorticoids Mitochondrial capacity is critical to adapt the high energy demand of the heart to circadian oscillations and diseased states. Glucocorticoids regulate the circadian cycle of energy metabolism, but little is known about how circadian timing of exogenous glucocorticoid dosing directly regulates heart metabolism through cardiomyocyte-autonomous mechanisms. While chronic oncedaily intake of glucocorticoids promotes metabolic stress and heart failure, we recently discovered that intermittent once-weekly dosing of exogenous glucocorticoids promoted muscle metabolism in normal and obese skeletal muscle. However, the effects of glucocorticoid intermittence on heart metabolism and heart failure remain unknown. Here we investigated the extent to which circadian time of dosing regulates the effects of the glucocorticoid prednisone in heart metabolism and function in conditions of single pulse or chronic intermittent dosing. In WT mice, we found that prednisone improved cardiac content of NAD+ and ATP with light-phase dosing (ZT0), while the effects were blocked by dark-phase dosing (ZT12). The drug effects on mitochondrial function were cardiomyocyte-autonomous, as shown by inducible cardiomyocyte-restricted glucocorticoid receptor (GR) ablation, and depended on an intact cardiomyocyte clock, as shown by inducible cardiomyocyte-restricted ablation of Brain and Muscle ARNT-like 1 (BMAL1). Conjugating time-of-dosing with chronic intermittence, we found that once-weekly prednisone improved metabolism and function in heart after myocardial injury dependent on circadian time of intake, i.e. with lightphase but not dark-phase dosing. Our study identifies cardiac-autonomous mechanisms through which circadian-specific intermittent dosing reconverts glucocorticoid drugs to metabolic boosters for the heart. A cell-based screen identifies HDAC inhibitors as activators of RIG-I signaling Enhancing the immune microenvironment in cancer by targeting the nucleic acid sensors is becoming a potent therapeutic strategy. Among the nucleic acid sensors, activation of the RNA sensor Retinoic Acid-inducible Gene (RIG-I) using small hairpin RNAs has been shown to elicit powerful innate and adaptive immune responses. Given the challenges inherent in pharmacokinetics and delivery of RNA based agonists, we set out to discover small molecule agonists of RIG-I using a cell-based assay. To this end, we established and validated a robust high throughput screening assay based on a commercially available HEK293 reporter cell line with a luciferase reporter downstream of tandem interferon stimulated gene 54 (ISG54) promoter elements. We first confirmed that the luminescence in this cell line is dependent on RIG-I and the interferon receptor using a hairpin RNA RIG-I agonist. We established a 96-well and a 384-well format HTS based on this cell line and performed a proof-of-concept screen using an FDA approved drug library of 1200 compounds. Surprisingly, we found two HDAC inhibitors Entinostat, Mocetinostat and the PLK1 inhibitor Volasertib significantly enhanced ISG-luciferase activity. This luminescence was substantially diminished in the null reporter cell line indicating the increase in signaling was dependent on RIG-I expression. Combination treatment of tumor cell lines with Entinostat increased RIG-I induced cell death in a mammary carcinoma cell line that is resistant to either Entinostat or RIG-I agonist alone. Taken together, our data indicates an unexpected role for HDAC1,-3 inhibitors in enhancing RIG-I signaling and highlight potential opportunities for therapeutic combinations. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development. Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments and Multiscale Models Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale, spatiotemporal models of cancer growth using state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns. Its implementation enabled us to pursue two goals; first, the quantitative description of the morphology of cancer progression in 3D cultures, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration. We applied this framework to the study of the spatiotemporal progression of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and accumulation, as well as random motion during the examined time period of development. To our knowledge, this is the first time that a multiscale model is used to quantify the relationship between the spatial patterns and the underlying mechanisms of cancer growth in 3D environments. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. Maf/ham1-like pyrophosphatases of non-canonical nucleotides are host-specific partners of viral RNA-dependent RNA polymerases Cassava brown streak disease (CBSD), dubbed the "Ebola of plants", is a serious threat to food security in Africa caused by two viruses of the family Potyviridae: cassava brown streak virus (CBSV) and Ugandan (U)CBSV. Intriguingly, U/CBSV, along with another member of this family and one secoviridae, are the only known RNA viruses encoding a protein of the Maf/ham1-like family, a group of widespread pyrophosphatase of non-canonical nucleotides (ITPase) expressed by all living organisms. Despite the socio-economic impact of CDSD, the relevance and role of this atypical viral factor has not been yet established. Here, using an infectious cDNA clone and reverse genetics, we demonstrate that UCBSV requires the ITPase activity for infectivity in cassava, but not in the model plant Nicotiana benthamiana. HPLC MS/MS experiments showed that, quite likely, this host-specific constraint is due to an unexpected high concentration of non-canonical nucleotides in cassava. Finally, protein analyses and experimental evolution of mutant viruses indicated that keeping a fraction of the yielded UCBSV ITPase covalently bound to the viral RNA-dependent RNA polymerase (RdRP) optimizes viral fitness, and this seems to be a feature shared by the other members of the Potyviridae family expressing Maf/ham1-like proteins. All in all, our work (i) reveals that the over-accumulation of non-canonical nucleotides in the host might have a key role in antiviral defense, and (ii) provides the first example of an RdRP-ITPase partnership, reinforcing the idea that RNA viruses are incredibly versatile at adaptation to different host setups. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Drug screening at single-organoid resolution via bioprinting and interferometry High-throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms for high-throughput screening use two-dimensional cultures of immortalized cell lines which do not accurately reflect the biology of human tumors. More clinically relevant model systems, such as three-dimensional tumor organoids, can be difficult to screen and scale. For example, manually seeded organoids coupled to destructive endpoint assays allow for the characterization of response to treatment, but do not capture the transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We therefore developed a pipeline to generate bioprinted tumor organoids linked to label-free, real-time imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D organoid structures that preserve tumor histology and gene expression. HSLCI imaging in tandem with machine learning-based image segmentation and organoid classification tools enables accurate, label-free parallel mass measurements for thousands of bioprinted organoids. We demonstrate that our method quantitatively identifies individual organoids as insensitive, transiently sensitive, or persistently sensitive to specific treatments. This opens new avenues for rapid, actionable therapeutic selection using automated tumor organoid screening. Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

MethodsWe propose a two-step approach to the analysis of a genetic association study: first, a set of variants that show evidence of association with the trait is used to estimate m; and second, the estimated m is used for log-F -penalized logistic regression analyses of all variants using data augmentation with standard software. Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation.

ResultsWe evaluate the statistical properties of our proposed two-step method and compared its performance to other shrinkage methods by a simulation study. Our simulation studies suggest that the proposed log-F -penalized approach has lower bias and mean squared error than other methods considered. We also illustrate the approach on data from a study of genetic associations with "super senior" cases and middle aged controls.

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach. Medium-throughput zebrafish optogenetic platform identifies deficits in subsequent neural activity following brief early exposure to cannabidiol and Δ-9-tetrahydrocannabinol In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. Mitochondrial genomes of two parasitic Cuscuta species lack clear evidence of horizontal gene transfer and retain unusually fragmented ccmFC genes BackgroundThe intimate association between parasitic plants and their hosts favours the exchange of genetic material, potentially leading to horizontal gene transfer (HGT) between plants. With the recent publication of several parasitic plant nuclear genomes, there has been considerable focus on such non-sexual exchange of genes. To enhance the picture on HGT events in a widely distributed parasitic genus, Cuscuta (dodders), we assembled and analyzed the organellar genomes of two recently sequenced species, C. australis and C. campestris, making this the first account of complete mitochondrial genomes (mitogenomes) for this genus.

ResultsThe mitogenomes are 265,696 and 275,898 bp in length and contain a typical set of mitochondrial genes, with ten missing or pseudogenized genes often lost from angiosperm mitogenomes. Each mitogenome also possesses a structurally unusual ccmFC gene, which exhibits splitting of one exon and a shift to trans-splicing of its intron. Based on phylogenetic analysis of mitochondrial genes from across angiosperms and similarity-based searches, there is little to no indication of HGT into the Cuscuta mitogenomes. A few candidate regions for plastome-to-mitogenome transfer were identified, with one suggestive of possible HGT.

ConclusionsThe lack of HGT is surprising given examples from the nuclear genomes, and may be due in part to the relatively small size of the Cuscuta mitogenomes, limiting the capacity to integrate foreign sequences. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Tracking the stochastic growth of bacterial populations in microfluidic droplets Bacterial growth in microfluidic droplets is relevant in biotechnology, in microbial ecology, and in understanding stochastic population dynamics in small populations. However, it has proved challenging to automate measurement of absolute bacterial numbers within droplets, forcing the use of proxy measures for population size. Here we present a microfluidic device and imaging protocol that allows high-resolution imaging of thousands of droplets, such that individual bacteria stay in the focal plane and can be counted automatically. Using this approach, we track the stochastic growth of hundreds of replicate Escherichia coli populations within droplets. We find that, for early times, the statistics of the growth trajectories obey the predictions of the Bellman-Harris model, in which there is no inheritance of division time. Our approach should allow further testing of models for stochastic growth dynamics, as well as contributing to broader applications of droplet-based bacterial culture. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. PKR-mediated Stress Response Enhances Dengue and Zika Virus Replication The mechanisms by which Flaviviruses use non-canonical translation to support their replication in host cells are largely unknown. Here we investigated how the integrated stress response (ISR), which promotes translational arrest by eIF2 phosphorylation (p-eIF2), regulates Flavivirus replication. During Dengue virus (DENV) and Zika virus (ZIKV) infection, eIF2 activation peaked at 24 hours post infection and was dependent on PKR but not type I interferon. The ISR is activated downstream of p-eIF2 during infection with either virus, but translation arrest only occurred following DENV infection. Despite this difference, both DENV and ZIKV replication was impaired in cells lacking PKR, independent of IFN-I/NF-kB signaling or cell viability. By using a ZIKV 5UTR reporter system as a model, we found that this region of the genome is sufficient to promote an enhancement of viral mRNA translation in the presence of an active ISR. Together we provide evidence that Flaviviruses escape ISR translational arrest and co-opt this response to increase viral replication. Interferon alpha-based combinations suppress SARS-CoV-2 and other viral infections There is an urgent need for new antivirals with powerful therapeutic potential and tolerable side effects. In the present study, we found that recombinant human interferon-alpha (IFNa) triggers intrinsic and extrinsic cellular antiviral responses, as well as reduces replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. Although IFNa alone was insufficient to completely abolish SARS-CoV-2 replication, combinations of IFNa with remdesivir or other antiviral agents (EIDD-2801, camostat, cycloheximide, or convalescent serum) showed strong synergy and effectively inhibited SARS-CoV-2 infection in human lung epithelial Calu-3 cells. Furthermore, we showed that the IFNa-remdesivir combination suppressed virus replication in human lung organoids, and that its single prophylactic dose attenuated SARS-CoV-2 infection in lungs of Syrian hamsters. Transcriptome and metabolomic analyses showed that the combination of IFNa-remdesivir suppressed virus-mediated changes in infected cells, although it affected the homeostasis of uninfected cells. We also demonstrated synergistic antiviral activity of IFNa2a-based combinations against other virus infections in vitro. Altogether, our results indicate that IFNa2a-based combination therapies can achieve higher efficacy while requiring lower dosage compared to monotherapies, making them attractive targets for further pre-clinical and clinical development. Deficits in seizure threshold and other behaviors in adult mice without gross neuroanatomic injury after late gestation transient prenatal hypoxia Intrauterine hypoxia is a common cause of brain injury in children resulting in a broad spectrum of long-term neurodevelopmental sequela, including life-long disabilities that can occur even in the absence of severe neuroanatomic damage. Postnatal hypoxia-ischemia rodent models are commonly used to understand the effects of ischemia and transient hypoxia on the developing brain. Postnatal models, however, have some limitations. First, they do not test the impact of placental pathologies on outcomes from hypoxia. Second, they primarily recapitulate severe injury because they provoke substantial cell death, which is not seen in children with mild hypoxic injury. Lastly, they do not model preterm hypoxic injury. Prenatal models of hypoxia in mice may allow us to address some of these limitations to expand our understanding of developmental brain injury. The published rodent models of prenatal hypoxia employ multiple days of hypoxic exposure or complicated surgical procedures, making these models challenging to perform consistently in mice. Furthermore, large animal models suggest that transient prenatal hypoxia without ischemia is sufficient to lead to significant functional impairment to the developing brain. However, these large animal studies are resource-intensive and not readily amenable to mechanistic molecular studies. Therefore, here we characterized the effect of late gestation (embryonic day 17.5) transient prenatal hypoxia (5% inspired oxygen) on long-term anatomical and neurodevelopmental outcomes in mice. Late gestation transient prenatal hypoxia increased hypoxia-inducible factor 1 alpha protein levels (a marker of hypoxic exposure) in the fetal brain. Hypoxia exposure predisposed animals to decreased weight at postnatal day 2, which normalized by day 8. However, hypoxia did not affect gestational age at birth, litter size at birth, or pup survival. No differences in fetal brain cell death or long-term gray or white matter changes resulted from hypoxia. Animals exposed to prenatal hypoxia did have several long-term functional consequences, including sex-dichotomous changes. Hypoxia exposure was associated with a decreased seizure threshold and abnormalities in hindlimb strength and repetitive behaviors in males and females. Males exposed to hypoxia had increased anxiety-related deficits, whereas females had deficits in social interaction. Neither sex developed any motor or visual learning deficits. This study demonstrates that late gestation transient prenatal hypoxia in mice is a simple, clinically relevant paradigm for studying putative environmental and genetic modulators of the long-term effects of hypoxia on the developing brain. Inference of an integrative, executable network for Rheumatoid Arthritis combining data-driven machine learning approaches and a state-of-the-art mechanistic disease map Rheumatoid arthritis (RA) is a multifactorial, complex autoimmune disease that involves various genetic, environmental and epigenetic factors. Systems biology approaches provide the means to study complex diseases through the integration of different layers of biological information. Combining multiple data types can help compensate for missing or conflicting information and limit the possibility of false positives. In this work, we aim to unravel mechanisms governing the regulation of key transcription factors in RA and derive patient-specific models to gain more insights into the disease heterogeneity and the response to treatment.

We first make use of publicly available transcriptomic datasets (peripheral blood) relative to RA and machine learning to create an RA specific transcription factor (TF) co-regulatory network. The TF cooperativity network is subsequently enriched in signalling cascades and upstream regulators using a state-of-the-art, RA-specific molecular map. The integrative network is then used as a template to analyze patients data regarding their response to anti-TNF treatment and identify master regulators and upstream cascades affected by the treatment. We use the Boolean formalism to simulate in silico subparts of the integrated network and identify combinations and conditions that can switch on or off the identified TFs, mimicking the effects of single and combined perturbations. Strength of interactions in the Notch gene regulatory network determines patterning and fate in the notochord Development of multicellular organisms requires the generation of gene expression patterns that determines cell fate and organ shape. Groups of genetic interactions known as Gene Regulatory Networks (GRNs) play a key role in the generation of such patterns. However, how the topology and parameters of GRNs determine patterning in vivo remains unclear due to the complexity of most experimental systems. To address this, we use the zebrafish notochord, an organ where coin-shaped precursor cells are initially arranged in a simple unidimensional geometry. These cells then differentiate into vacuolated and sheath cells. Using newly developed transgenic tools together with in vivo imaging, we identify jag1a and her6/her9 as the main components of a Notch GRN that generates a lateral inhibition pattern and determines cell fate. Making use of this experimental system and mathematical modeling we show that lateral inhibition patterning requires that ligand-receptor interactions are stronger within the same cell than in neighboring cells. Altogether, we establish the zebrafish notochord as an experimental system to study pattern generation, and identify and characterize how the properties of GRNs determine self-organization of gene patterning and cell fate. Estimating animal density with camera traps: a practitioner's guide of the REST model Camera traps are increasingly popular in wildlife research and have the potential to be reliable and cost-effective for estimating animal density. Although density estimation using this automatic technique has long been restricted to species with individually recognizable markings, several analytical approaches have been proposed to target animals lacking such markings (i.e., unmarked populations). Among these approaches, the random encounter and staying time (REST) model may be an efficient and cost-effective approach, even though the procedures for the implementations have not yet been shared with researchers. This paper presents a working protocol for implementing the REST model our research group has been developing. We also present the R code to perform parameter estimation with a maximum likelihood and Bayesian approach. We suggest that this model has potential for further development. We strongly hope that this paper will encourage many researchers to use the REST for density estimation in a wide variety of species in various habitats and make a significant contribution to advancing wildlife conservation and management. Extensive duplication and convergent evolution of an antimicrobial peptide gene Antimicrobial peptides (AMPs) are host-encoded antibiotics that combat invading pathogens. These genes commonly encode multiple products as post-translationally cleaved polypeptides. Recent studies have highlighted roles for AMPs in neurological contexts suggesting functions for these defence molecules beyond infection. During our immune study characterizing the antimicrobial peptide gene Baramicin, we recovered multiple Baramicin paralogs in Drosophila melanogaster and other species, united by their N-terminal IM24 domain. Not all paralogs were immune-induced. Here, through careful dissection of the Baramicin familys evolutionary history, we find that these non-immune paralogs result from repeated events of duplication and subsequent truncation of the coding sequence from an immune-inducible ancestor. These truncations leave only the IM24 domain as the prominent gene product. Surprisingly, using mutation and targeted gene silencing we demonstrate that two such genes are adapted for function in neural contexts in D. melanogaster. We also show enrichment in the head for independent Baramicin genes in other species. The Baramicin evolutionary history reveals that the IM24 Baramicin domain is not strictly useful in an immune context. We thus provide a case study for how an AMP-encoding gene might play dual roles in both immune and non-immune processes via its multiple peptide products. We reflect on these findings to highlight a blind spot in the way researchers approach AMP research in in vivo contexts.

Significance statementAntimicrobial peptides are immune proteins recently implicated in neurological roles. To date little attention has been paid to the contributions of different gene products in this function. Here we show that an antimicrobial peptide gene encodes multiple products with either immune-specific or neurological roles. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis.