The LOTUS Initiative for Open Natural Products Research: Knowledge Management through Wikidata Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base.

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BatchDTA: Implicit batch alignment enhances deep learning-based drug-target affinity estimation Candidate compounds with high binding affinities toward a target protein are likely to be developed as drugs. Deep neural networks (DNNs) have attracted increasing attention for drug-target affinity (DTA) estimation owning to their efficiency. However, the negative impact of batch effects caused by measure metrics, system technologies, and other assay information is seldom discussed when training a DNN model for DTA. Suffering from the data deviation caused by batch effects, the DNN models can only be trained on a small amount of "clean" data. Thus, it is challenging for them to provide precise and consistent estimations. We design a batch-sensitive training framework, namely BatchDTA, to train the DNN models. BatchDTA implicitly aligns multiple batches toward the same protein, alleviating the impact of the batch effects on the DNN models. Extensive experiments demonstrate that BatchDTA facilitates four mainstream DNN models to enhance the ability and robustness on multiple DTA datasets. The average concordance index (CI) of the DNN models achieves a relative improvement of 4.0%. BatchDTA can also be applied to the fused data collected from multiple sources to achieve further improvement.
Prostaglandin EP3 Receptor signaling is required to prevent insulin hypersecretion and metabolic dysfunction in a non-obese mouse model of insulin resistance When homozygous for the LeptinOb mutation (Ob), Black-and-Tan Brachyury (BTBR) mice become morbidly obese and severely insulin resistant, and by 10 weeks of age, frankly diabetic. Previous work has shown Prostaglandin EP3 Receptor (EP3) expression and activity is up-regulated in islets from BTBR-Ob mice as compared to lean controls, actively contributing to their beta-cell dysfunction. In this work, we aimed to test the impact of beta-cell-specific EP3 loss on the BTBR-Ob phenotype by crossing Ptger3 floxed mice with the Rat insulin promoter (RIP)-CreHerr driver strain. Instead, germline recombination of the floxed allele in the founder mouse - an event whose prevalence we identified as directly associated with underlying insulin resistance of the background strain - generated a full-body knockout. Full-body EP3 loss provided no diabetes protection to BTBR-Ob mice, but, unexpectedly, significantly worsened BTBR-lean insulin resistance and glucose tolerance. This in vivo phenotype was not associated with changes in beta-cell fractional area or markers of beta-cell replication ex vivo. Instead, EP3-null BTBR-lean islets had essentially uncontrolled insulin hypersecretion. The selective up-regulation of constitutively-active EP3 splice variants in islets from young, lean BTBR mice as compared to C57BL/6J, where no phenotype of EP3 loss has been observed, provides a potential explanation for the hypersecretion phenotype. In support of this, high islet EP3 expression in Balb/c females vs. Balb/c males was fully consistent with their sexually-dimorphic metabolic phenotype after loss of EP3-coupled Gz protein. Taken together, our findings provide a new dimension to the understanding of EP3 as a critical brake on insulin secretion.

New and NoteworthyIslet Prostaglandin EP3 receptor (EP3) signaling is well-known as up-regulated in the pathophysiological conditions of type 2 diabetes, contributing to beta-cell dysfunction. Unexpected findings in mouse models of non-obese insulin sensitivity and resistance provide a new dimension to our understanding of EP3 as a key modulator of insulin secretion. A previously-unknown relationship between mouse insulin resistance and the penetrance of Rat insulin promoter-driven germline floxed allele recombination is critical to consider when creating beta-cell-specific knockouts.

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org.highwire.dtl.DTLVardef@15cf1d5org.highwire.dtl.DTLVardef@108f565org.highwire.dtl.DTLVardef@126e479org.highwire.dtl.DTLVardef@61fdf8_HPS_FORMAT_FIGEXP  M_FIG C_FIG "Adopt a Microorganism" methodology enhances the discourse richness of high school students in both hybrid learning and remote education The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. The structurome of a Clostridium difficile phage and the remarkable accurate prediction of its novel phage receptor-binding protein As natural bacterial predators, bacteriophages have the potential to be developed to tackle antimicrobial resistance, but our exploitation of them is limited by understanding their vast uncharacterised genetic diversity1,2. Fascinatingly, this genetic diversity reflects many ways that phages can make proteins, performing similar functions that together form the familiar phage particle. Critical to infection are phage receptor-binding proteins (RBPs) that bind bacterial  receptors and initiate bacterial entry3. Here we identified and characterised Gp22, a novel RBP for phage CDHS-1 that infects pathogenic C. difficile, but that had no recognisable RBPs. We showed that Gp22 antibodies neutralised CDHS-1 infection and used immunogold-labelling and transmission electron microscopy to identify their location on the capsid. The Gp22 three-dimensional structure was resolved by X-ray crystallography revealing a new RBP class with an N-terminal L-shaped -helical superhelix domain and a C-terminal Mg2+-binding domain. The findings provide novel insights into C. difficile phage biology and phage-host interactions. This will facilitate optimal phage development and future engineering strategies4,5. Furthermore, the AlphaFold2-predicted Gp22 structure, which was strikingly accurate, paves the way for a structurome based transformation and guidance of future phage studies where many proteins lack sequence homology but have recognisable protein structures. 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. Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics Data There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

Author summaryReconstruction of multiple association networks from high dimensional omics data is an important topic, especially in biology. Previous studies focused on estimating different networks and detecting common hubs among all classes. Integration of information over different classes of data while allowing difference in the hub nodes is also biologically plausible. Therefore, we propose a method, EDOHA, to jointly construct multiple interaction networks with capacity in finding different hub networks for each class of data. Simulation studies show the better performance over conventional methods. The method has been demonstrated in three real world data. Excitatory and inhibitory motor cortical clusters account for balance, variability, and task performance Behaving animals have to process partial or incomplete information to plan movements. Neural activity and behavior of highly trained animals are strikingly variable across behavioral trials. In the present study, we show that incomplete information is reflected in both neural and behavioral variability. We study a mechanism for such variability in spiking neural network models with cluster topologies that enables multistability and attractor dynamics. Multistable attractors have been studied in spiking neural networks through clusters of strongly interconnected excitatory neurons. However, we show that existing models suffer from weak robustness and fail to reproduce the experimental findings. To overcome these problems, we introduce a novel architecture with excitatory and inhibitory clusters of spiking neurons. In contrast to earlier prominent models of excitatory clusters, this model ensures the local balance of excitation and inhibition and shows robust multistability across a wide range of network parameters. Furthermore, with the appropriate stimulation of network clusters, this network topology enables qualitatively and quantitatively reproducing in vivo firing rates, variability dynamics and behavioral reaction times for different task conditions as observed in recordings from the motor cortex of behaving monkeys. Social behavioral profiling by unsupervised deep learning reveals a stimulative effect of dopamine D3 agonists on zebrafish sociality It has been a major challenge to systematically evaluate and compare how pharmacological perturbations influence social behavioral outcomes. Although some pharmacological agents are known to alter social behavior, precise description and quantification of such effects have proven difficult. The complexity of brain functions regulating sociality makes it challenging to predict drug effects on social behavior without testing in live animals, and most existing behavioral assays are low-throughput and provide only unidimensional readouts of social function. To achieve richer characterization of drug effects on sociality, we developed a scalable social behavioral assay for zebrafish named ZeChat based on unsupervised deep learning. High-dimensional and dynamic social behavioral phenotypes are automatically classified using this method. By screening a neuroactive compound library, we found that different classes of chemicals evoke distinct patterns of social behavioral fingerprints. By examining these patterns, we discovered that dopamine D3 agonists possess a social stimulative effect on zebrafish. The D3 agonists pramipexole, piribedil, and 7-hydroxy-DPAT-HBr rescued social deficits in a valproic acid-induced zebrafish autism model. The ZeChat platform provides a promising approach for dissecting the pharmacology of social behavior and discovering novel social-modulatory compounds. Capturing the interplay of membrane lipids and structural transitions in human ABCA7 Phospholipid extrusion by ABC subfamily A (ABCA) exporters is central to cellular physiology, although the specifics of the underlying substrate interactions and transport mechanisms remain poorly resolved at the molecular level. Here we report cryo-EM structures of lipid-embedded human ABCA7 in an open state and a nucleotide-bound, closed state at resolutions between 3.6-4.0 [A]. The former reveals an ordered patch of bilayer lipids traversing the transmembrane domain (TMD), while the latter reveals a lipid-free, closed TMD with a small extracellular opening. These structures offer a structural framework for both substrate entry and exit from the ABCA7 TMD and highlight conserved rigid-body motions that underlie the associated conformational transitions. Combined with functional analysis and molecular dynamics (MD) simulations, our data also shed light on lipid partitioning into the ABCA7 TMD and localized membrane perturbations that underlie ABCA7 function and have broader implications for other ABCA family transporters. Glypiated FGF directs contact-mediated bidirectional signaling to self-regulate tissue-specific dispersion How signaling proteins generate a multitude of information to organize tissue patterns is critical to understanding morphogenesis. In Drosophila, FGF produced in wing-disc cells regulates the development of the disc-associated air-sac-primordium (ASP). Here, we show that FGF is Glycosylphosphatidylinositol-anchored to the producing cell surface and that this modification both inhibits free FGF secretion and activates target-specific bidirectional FGF-FGFR signaling through cytonemes. FGF-source and recipient ASP cells extend cytonemes that present FGF and FGFR on their surfaces and reciprocally recognize each other over distance by contacting through CAM-like FGF-FGFR binding. Contact-mediated FGF-FGFR binding induces bidirectional signaling, which, in turn, promotes ASP and source cells to polarize cytonemes toward each other and reinforce signaling contacts. Subsequent un-anchoring of FGFR-bound-FGF from the source cell membrane dissociates cytoneme contacts and delivers FGF target-specifically to ASP cytonemes for paracrine functions. Thus, GPI-anchored FGF organizes both source and recipient cells and self-regulates its cytoneme-mediated tissue-specific dispersion and signaling. Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors? As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Determination of adequate sample size requires (i) knowledge of the detection ability of the inference method being used, and (ii) a consideration of the smallest biologically meaningful deviation from the null expectation. However, (i) has not been investigated and (ii) is yet to be discussed. Consequently, typical experimental sample sizes are small (3-4 replicates), except for some individual-level studies where replicates may exceed 100. Re-analysis of recently published data highlights how small sample sizes can only detect very large deviations from the null model, implying many important non-null stressor-pair interactions are being missed, and how sample size only improves detection ability slowly. Critically, researchers still need to define the smallest interaction of interest, i.e. the lower limit for a biologically important interaction, which is likely to be system specific, meaning that a general guide is unavailable. However, we suspect that most experiments may require 20 or more replicates per treatment. Sample sizes could potentially be increased by focussing on individual-level responses to multiple stressors, or by forming coordinated networks of researchers to repeat experiments in larger-scale studies. Our analyses relate to the additive and multiplicative null models and we encourage similar analyses on other null models and inference methods for stressor interactions. Without knowledge of the detection abilities of the statistical tools at hand, or definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. Chromosome fusion affects genetic diversity and evolutionary turnover of functional loci, but consistently depends on chromosome size Major changes in chromosome number and structure are linked to a series of evolutionary phenomena, including intrinsic barriers to gene flow or suppression of recombination due to chromosomal rearrangements. However, chromosome rearrangements can also affect the fundamental dynamics of molecular evolution within populations by changing relationships between linked loci and altering rates of recombination. Here, we build chromosome-level assembly Eueides isabella and, together with the chromosome-level assembly of Dryas iulia, examine the evolutionary consequences of multiple chromosome fusions in Heliconius butterflies. These assemblies pinpoint fusion points on 10 of the 21 autosomal chromosomes and reveal striking differences in the characteristics of fused and unfused chromosomes. The ten smallest autosomes in D. iulia and E. isabella, which have each fused to a longer chromosome in Heliconius, have higher repeat and GC content, and longer introns than predicted by their chromosome length. Following fusion, these characteristics change to become more in line with chromosome length. The fusions also led to reduced diversity, which likely reflects increased background selection and selection against introgression between diverging populations, following a reduction in per-base recombination rate. We further show that chromosome size and fusion impact turnover rates of functional loci at a macroevolutionary scale. Together these results provide further evidence that chromosome fusion in Heliconius likely had dramatic effects on population level processes shaping rates of neutral and adaptive divergence. These effects may have impacted patterns of diversification in Heliconius, a classic example of an adaptive radiation. Lmo7 recruits myosin II heavy chain to induce apical constriction in Xenopus ectoderm Apical constriction, or reduction of the apical domain, underlies many morphogenetic events during development, such as furrow or tube formation. Actomyosin complexes play an essential role in apical constriction, however the detailed analysis of molecular mechanisms is still pending. Here we show that Lim domain only protein 7 (Lmo7), a multidomain adaptor at apical junctions, promotes apical constriction in the Xenopus superficial ectoderm, whereas apical domain size increases in Lmo7-depleted cells. Lmo7 is localized to and promotes the formation of the circumferential actomyosin belt adjacent to apical junctions. We find that Lmo7-dependent apical constriction requires the RhoA-ROCK-Non-muscle myosin II (NMII) pathway. Strikingly, Lmo7 binds and recruits NMII heavy chains to apical junctions. Lmo7 overexpression altered the subcellular distribution of Wtip, a sensor of mechanical tension. Our findings suggest that Lmo7 serves as a scaffold organizing the actomyosin network to regulate contractility at apical junctions. Bioactive constituents of Verbena officinalis regulate killing efficiency of primary human natural killer cells by accelerating killing processes BackgroundNatural killer (NK) cells play a key role in eliminating tumorigenic and pathogen-infected cells. Verbena officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine, exhibiting anti-tumor and anti-inflammation activity, but its role in NK cells remains unclear.

PurposeThe impact of bioactive constituents of V. officinalis on immune responses remains largely elusive. In this work we investigated the potential targets of V. officinalis and focused on killing efficiency and related functions of NK cells regulated by bioactive constituents of V. officinalis.

Study design/methodsWe used primary human NK cells from peripheral blood mononuclear cells. Potential regulatory roles of selected compounds in NK killing function-related genes were first analyzed by network pharmacology approaches. Potential engagement between compounds and NK receptors was examined by molecular docking assay. Killing efficiency of NK cells was determined with real-time killing assay and live-cell imaging. Proliferation was examined by CFSE staining. Expression of cytotoxic proteins was analyzed using flow cytometry. Lytic granule release was quantified by CD107a degranulation assay. Contact time required for killing and determination of serial killers were analyzed using live cell imaging results.

ResultsResults from network pharmacology approaches and molecular docking analyses predicted that the five bioactive compounds (acteoside, apigenin, kaempferol, verbenalin and hastatoside) from V. officinalis can regulated various key genes essential for NK effector functions and can bind to NK inhibitory receptors as well as activating receptors, indicating their potential role in regulating NK killing capacity. Analyses of NK killing efficiency revealed that out of these five compounds verbenalin exhibited an encouraging potency to enhance NK killing efficiency. Further investigation showed that verbenalin did not affect proliferation, expression of cytotoxic proteins, or lytic granule degranulation, but rather reduced contact time required for killing, enhanced total killing events per NK cell, and elevated the fraction of killing competent NK cells.

ConclusionsIn this work, we have identified verbenalin as the most potent bioactive constituent from V. officinalis to enhance NK cell killing efficiency via accelerating killing processes and converting non-killers to killing competent NK cells without affecting the lytic granule pathway. Identification of a conserved neutralizing epitope present on spike proteins from all highly pathogenic coronaviruses Three pathogenic human coronaviruses have emerged within the last 20 years, with SARS-CoV-2 causing a global pandemic. Although therapeutic antibodies targeting the SARS-CoV-2 spike currently focus on the poorly conserved receptor-binding domain, targeting essential neutralizing epitopes on the more conserved S2 domain may provide broader protection. We report an antibody binding an epitope conserved in the pre-fusion core of MERS-CoV, SARS-CoV and SARS-CoV-2 spike S2 domains. Antibody 3A3 binds a conformational epitope with ~2.5 nM affinity and neutralizes spike from SARS-CoV, SARS-CoV-2 and variants of concern in in vitro pseudovirus assays. Hydrogen-deuterium exchange mass spectrometry identified residues 980-1006 in the flexible hinge region at the S2 apex as the 3A3 epitope, suggesting 3A3 prevents the S2 conformational rearrangements required for conversion to the spike post-fusion state and virus-host cell fusion. This work defines a conserved vulnerable site on the SARS-CoV-2 S2 domain and guides the design of pan-protective spike immunogens. Swine H1N1 influenza virus variants with enhanced polymerase activity and HA stability promote airborne transmission in ferrets Understanding how animal influenza A viruses (IAVs) acquire airborne transmissibility in humans and ferrets is needed to prepare for and respond to pandemics. Here, we investigated in ferrets the replication and transmission of swine H1N1 isolates P4 and G15, whose majority population had decreased polymerase activity and poor HA stability, respectively. For both isolates, a minor variant was selected and transmitted in ferrets. Polymerase-enhancing variant PA-S321 airborne-transmitted and propagated in one ferret. HA-stabilizing variant HA1-S210 was selected in all G15-inoculated ferrets and was transmitted by contact and airborne routes. With an efficient polymerase and a stable HA, the purified minor variant G15-HA1-S210 had earlier and higher peak titers in inoculated ferrets and was recovered at a higher frequency after airborne transmission than P4 and G15. Overall, HA stabilization played a more prominent role than polymerase enhancement in the replication and transmission of these viruses in ferrets. The results suggest pandemic risk-assessment studies may benefit from deep sequencing to identify minor variants with human-adapted traits.

IMPORTANCEDiverse IAVs circulate in animals, yet few acquire the viral traits needed to start a human pandemic. A stabilized HA and mammalian-adapted polymerase have been shown to promote the adaptation of IAVs to humans and ferrets (the gold-standard model for IAV replication, pathogenicity, and transmissibility). Here, we used swine IAV isolates of the gamma lineage a model to investigate the importance of HA stability and polymerase activity in promoting replication and transmission in ferrets. These are emerging viruses that bind to both -2,6- and -2,3-linked receptors. Using isolates containing mixed populations, a stabilized HA was selected within days in inoculated ferrets. An enhanced polymerase was also selected and propagated after airborne transmission to a ferret. Thus, HA stabilization was a stricter requirement, yet both traits promoted transmissibility. Knowing the viral traits needed for pandemic potential, and the relative importance of each, will help identify emerging viruses of greatest concern. 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. A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. Elucidation of global and local genomic epidemiology of Salmonella enterica  Enteritidis through multilevel genome typing Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26,670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA were identified; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018, revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified MDR associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.

Impact statementSalmonella enterica serovar Enteritidis is a common foodborne pathogen that can cause large outbreaks. Surveillance and high-resolution typing are essential for outbreak prevention and control. Genome sequencing offers unprecedented power for these purposes and a standardised method or platform for the interpretation, comparison and communication of genomic typing data is highly desirable. In this work, we developed a genomic typing scheme called Multilevel Genome Typing (MGT) for S. Enteritidis. We analysed 26,670 publicly available genomes of S. Enteritidis using MGT. We characterised the geographic and temporal distribution of S. Enteritidis MGT types as well as their association with multidrug resistance (MDR) and virulence genes. A publicly available MGT database for S. Enteritidis was established, which has the potential facilitate the unified global public health surveillance for this pathogen.

Data SummaryO_LIThe MGT database for S. Enteritidis is available at https://mgtdb.unsw.edu.au/enteritidis/.
C_LIO_LIAll accession numbers of the public available genomes were available in the MGT database and Data Set S1, Tab 1. And there were no newly sequenced data in this study.
C_LIO_LISupplementary material: Supplementary Fig. S1 to S7, supplementary methods and supporting results about the evaluation of potential repeat sequencing bias.
C_LIO_LIData Set S1: Supporting tables of the main results.
C_LIO_LIData Set S2. Supporting tables of the repeat sequencing bias evaluation by removing the potential repeat sequencing isolates. Note outbreak isolates may also be removed.
C_LI Transcripts switched off at the stop of phloem unloading highlight the energy efficiency of sugar import in the ripening V. vinifera fruit. Transcriptomic changes at the cessation of sugar accumulation in the pericarp of Vitis vinifera were addressed on single berries re-synchronized according to their individual growth patterns. The net rates of water, sugars and K+ accumulation inferred from individual growth and solute concentration confirmed that these inflows stopped simultaneously in the ripe berry, while the small amount of malic acid remaining at this stage was still being oxidized at low rate. Re-synchronized individual berries displayed negligible variations in gene expression among triplicates. RNA-Seq studies revealed sharp reprogramming of cell wall enzymes and structural proteins at the stop of phloem unloading, associated with an 80% repression of multiple sugar transporters and aquaporins on the plasma or tonoplast membranes, with the noticeable exception of H+/sugar symporters, that were rather weakly and constitutively expressed. This was verified in three genotypes placed in contrasted thermo-hydric conditions. The prevalence of SWEET suggests that electrogenic transporters would play a minor role on the plasma membranes of SE/CC complex and the one of the flesh, while sucrose/H+ exchangers dominate on its tonoplast. Cis-regulatory elements present in their promoters allowed to sort these transporters in different groups, also including specific TIPs and PIPs paralogs, and cohorts of cell wall related genes. Together with simple thermodynamic considerations, these results lead to propose that H+/sugar exchangers at the tonoplast, associated with a considerably acidic vacuolar pH, may exhaust cytosolic sugars in the flesh and alleviate the need for supplementary energization of sugar transport at the plasma membrane. An exploratory study on the role of the stiffness of breast cancer cells in their detachment from spheroids and migration in 3D collagen matrices BackgroundTumour-cell detachment is a critical early event in the metastatic cascade. However, the role of the cells mechanical properties in detachment and migration is not well understood. This exploratory study aimed to assess how intracellular stiffness changes these processes.

MethodsMDA-MB-231 cells were embedded as 10,000-cell spheroids in 2 and 4 mg/ml collagen matrices. Intracellular stiffness was assessed with mitochondria tracking microrheology of cells that migrated distances equivalent to four and six times the cell diameter (dC) from the spheroid and compared to cells at the spheroid surface (0dC), representing medium, high and no migration, respectively.

Results and discussionThe mitochondrial mean square displacement and intracellular stiffness decreased during detachment and migration for both collagen concentrations (i.e. rigidities). The mean square displacement of 4dC and 6dC cells was similar, whereas cell stiffness was lower for 4dC than for 6dC cells. With increasing matrix rigidity, the intracellular stiffness decreased for 0dC cells and did not change for 4dC and 6dC cells. It is proposed that decreased cell stiffness drives detachment and migration and increased matrix rigidity physically hinders migration, and cells need to become softer or remodel the environment to migrate. The independence of the stiffness of migrated cells from matrix rigidity suggests that cells remodel their environment through matrix proteins cleavage to migrate.

ConclusionsThe study revealed the collective effects of enhanced migratory conditions and increased matrix rigidity on the mechanical properties of the cells. The expression of matrix metalloproteinases and transforming growth factor {beta} and the role of cell volume on detachment and migration in matrices with varying pore sizes are proposed targets for further studies on metastatic cancer cells. Generation of nonlinear and spatially-organized 3D cultures on a microfluidic chip using photoreactive thiol-ene and methacryloyl hydrogels Micropatterning techniques for 3D cell cultures enable the recreation of tissue-level structures, but their combination with well-defined, microscale fluidic systems for perfusion remains challenging. To address this technological gap, we developed a user-friendly in-situ micropatterning protocol that integrates photolithography of crosslinkable, cell-laden hydrogels with a simple microfluidic housing, and tested the impact of crosslinking chemistry on stability and spatial resolution. Working with gelatin functionalized with photo-crosslinkable moieties, we found that inclusion of cells at high densities ([&ge;] 107/mL) during crosslinking did not impede thiol-norbornene gelation, but decreased the storage moduli of methacryloyl hydrogels. Hydrogel composition and light dose were selected to match the storage moduli of soft tissues. The cell-laden precursor solution was flowed into a microfluidic chamber and exposed to 405 nm light through a photomask to generate the desired pattern. The on-chip 3D cultures were self-standing, and the designs were interchangeable by simply swapping out the photomask. Thiol-ene hydrogels yielded highly accurate feature sizes from 100 - 900 m in diameter, whereas methacryloyl hydrogels yielded slightly enlarged features. Furthermore, only thiol-ene hydrogels were mechanically stable under perfusion overnight. Repeated patterning readily generated multi-region cultures, either separately or adjacent, including non-linear boundaries that are challenging to obtain on-chip. As a proof-of-principle, primary human T cells, were patterned on-chip with high regional specificity. Viability remained high (> 85%) after overnight culture with constant perfusion. We envision that this technology will enable researchers to pattern 3D cultures under fluidic control in biomimetic geometries that were previously difficult to obtain. Reconstitution of minimal motility system based on Spiroplasma swimming by expressing two bacterial actins in synthetic minimal bacterium Motility is one of the most important features of life, but its evolutionary origin remains unknown. In this study, we focused on Spiroplasma, commensal, or parasitic bacteria. They swim by switching the helicity of a ribbon-like cytoskeleton that comprises six proteins, each of which evolved from a nucleosidase and bacterial actin called MreB. We expressed these proteins in a synthetic, non-motile minimal bacterium, JCVI-syn3.0B, whose reduced genome was computer-designed and chemically synthesized. The synthetic bacterium exhibited swimming motility with features characteristic of Spiroplasma swimming. Moreover, some combinations of the two proteins produced a helical cell shape and swimming, suggesting that the swimming originated from the differentiation and coupling of bacterial actins, and we also obtained a minimal system for motility of the synthetic bacterium.

One-Sentence SummaryThe minimal system comprised two bacterial actins that provided cell helicity and swimming to the synthetic minimal bacterium. Genome-wide analysis of the non-coding RNA synthetic genetic network reveals extensive plasticity and unique phenotypes in yeast Recent studies identified non-coding RNAs (ncRNAs) with unknown function that are responsible for major fitness changes in yeast. To understand ncRNA interplay and aid their functional assignment, the synthetic genetic array (SGA) methodology was employed to create >15,000 double mutants and to score their epistasis in different environments. Unlike the protein network, ncRNAs mostly displayed positive epistasis in rich medium. Interestingly, the negative interactions significantly increased under stressors, showing environmental-dependent functions for ncRNAs. No correlation was found between the network of ncRNAs and that of their neighbouring genes, suggesting functional independence. The U3 paralogs, SNR17A and SNR17B, share the majority of genetic interactions in rich medium as expected. For example, SUT480 interacted with both paralogs and its function was linked to 18S rRNA processing. However, under stressors, a large number of unique epistatic interactions were observed, supporting the notion that SNR17A and SNR17B have diverged and sub-functionalised after genome duplication.