Human 14-3-3 proteins site-selectively bind the mutational hotspot region of SARS-CoV-2 nucleoprotein modulating its phosphoregulation Phosphorylated within its Ser/Arg-rich region, the SARS-CoV-2 nucleoprotein (N) recruits the phosphopeptide-binding human 14-3-3 proteins that play a well-recognized role in replication of many viruses. Here we use genetic code expansion to demonstrate that phosphorylation of SARS-CoV-2 N at either of two pseudo-repeats centered at Ser197 and Thr205 is sufficient for 14-3-3 binding. According to fluorescence anisotropy, the pT205-motif, present in SARS-CoV-2 but not in SARS-CoV, is preferred over the pS197-motif by all seven human 14-3-3 isoforms, which display unforeseen pT205/pS197 binding selectivity hierarchy. Crystal structures demonstrate that pS197 and pT205 are mutually exclusive 14-3-3-binding sites, whereas SAXS and biochemical data indicate 14-3-3 binding occludes the Ser/Arg-rich region, inhibiting its dephosphorylation. This Ser/Arg-rich region of N is highly prone to mutations, as exemplified by the Omicron and Delta variants, with our data suggesting how the strength of its 14-3-3 binding can be linked with the replicative fitness of the virus.
Active antithrombin glycoforms are selectively physiosorbed on plasma extracellular vesicles Antithrombin (AT) is a glycoprotein produced by the liver and a principal antagonist of active clotting proteases. A deficit in AT function leads to AT qualitative deficiency, challenging to diagnose. Here we report that active AT may travel physiosorbed on the surface of plasma extracellular vesicles (EVs), contributing to form the "EV-protein corona". The corona is enriched in specific AT glycoforms, thus suggesting glycosylation to play a key role in AT partitioning between EVs and plasma. Differences in AT glycoform composition of the corona of EVs separated from plasma of healthy and AT qualitative deficiency-affected subjects were also noticed. This suggests deconstructing the plasma into its nanostructured components, as extracellular vesicles, could help to unravel pathophysiological mechanisms otherwise undiscovered.
Conformational decoupling in acid-sensing ion channels uncovers mechanism and stoichiometry of PcTx1-mediated inhibition Acid-sensing ion channels (ASICs) are trimeric proton-gated cation channels involved in fast synaptic transmission. Pharmacological inhibition of ASIC1a reduces neurotoxicity and stroke infarct volumes, with the cysteine knot toxin Psalmotoxin-1 (PcTx1) being one of the most potent and selective inhibitors. PcTx1 binds at the subunit interface in the extracellular domain (ECD), but the mechanism and conformational consequences of the interaction, as well as the number of toxin molecules required for inhibition remain unknown. Here we use voltage-clamp fluorometry and subunit concatenation to decipher the mechanism and stoichiometry of PcTx1 inhibition of ASIC1a. Besides the known inhibitory binding mode, we propose PcTx1 to have at least two additional binding modes that are decoupled from the pore. One of these modes induces a long-lived ECD conformation that reduces the activity of an endogenous neuropeptide. This long-lived conformational state is proton-dependent and can be destabilized by a mutation that decreases PcTx1 sensitivity. Lastly, the use of concatemeric channel constructs reveal that disruption of a single PcTx1 binding site is sufficient to destabilize the toxin-induced conformation, while functional inhibition is not impaired until two or more binding sites are mutated. Together, our work provides insight into the mechanism of PcTx1 inhibition of ASICs and uncovers a prolonged conformational change with possible pharmacological implications. The mechanism of full activation of tumor suppressor PTEN at the phosphoinositide-enriched membrane Tumor suppressor PTEN, the second most highly mutated protein in cancer, dephosphorylates signaling lipid PIP3 produced by PI3Ks. Excess PIP3 promotes cell proliferation. The mechanism at the membrane of this pivotal phosphatase is unknown hindering drug discovery. Exploiting explicit solvent simulations, we tracked full-length PTEN trafficking from the cytosol to the membrane. We observed its interaction with membranes composed of zwitterionic phosphatidylcholine, anionic phosphatidylserine, and phosphoinositides, including signaling lipids PIP2 and PIP3. We tracked its moving away from the zwitterionic and getting absorbed onto anionic membrane that harbors PIP3. We followed it localizing on microdomains enriched in signaling lipids, as PI3K does, and observed PIP3 allosterically unfolding the N-terminal PIP2 binding domain, positioning it favorably for the polybasic motif interaction with PIP2. Finally, we determined PTEN catalytic action at the membrane, all in line with experimental observations, deciphering the mechanisms of how PTEN anchors to the membrane and restrains cancer. The multi-level phenotypic impact of synonymous substitutions: heterologous gene expression in human cells. Redundancy in the genetic code allows for differences in transcription and/or translation efficiency between sequences carrying synonymous polymorphisms, potentially leading to phenotypic changes. It is commonly admitted that the evolution codon usage bias ("CUB", the over-representation of certain codons in a genome, a gene or in positions along a gene) are driven by a combination of neutral and selective processes, but their relative contribution is a matter of debate, especially in mammals. Particularly, integrative studies quantifying the phenotypic impact of CUB at different molecular and cellular levels are lacking. Here we report a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells.

Six synonymous versions of the shble antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was assessed by means of: i) mRNA-to-DNA and protein-to-mRNA ratios for each shble version; ii) cellular fluorescence, using flow cytometry, as a proxy for single-cell level expression; and iii) real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness.

We show that differences in CUB strongly impact the molecular and the cellular phenotype: i) they result in large differences in mRNA and in protein levels, as well in mRNA-to-protein ratio; ii) they introduce splicing events not predicted by current algorithms; iii) they lead to reproducible phenotypic heterogeneity; iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression.

We interpret that CUB modulate mRNA availability and suitability for translation in human cells, leading to differences in protein levels and eventually eliciting phenotypic differences.

AUTHOR SUMMARYThe genetic code is redundant, with several codons encoding for the same amino acid. These synonymous codons are not used with equal frequencies. Instead, codon usage bias (CUB) varies between species, genes, and even positions along a gene. At each of these levels, CUB are shaped by the overall balance between mutational biases and selection forces. To shed light on the molecular mechanisms underlying molecular and organism phenotypes, integrative studies quantifying the phenotypic impact of CUB at different levels of biological integration are necessary. Here, we monitored the multiscale changes induced by six synonymous versions of an antibiotic resistance gene independently expressed in a human cell line. We show that: 1. both mRNA levels, protein levels, and their ratios are affected by CUB; 2. potential effects on mRNA (splicing and availability for translation) seem to constitute the main level of action; 3. cell fitness is severely impacted by a trade-off between the burden of heterologous expression and the benefits of antibiotic resistance. This integrative study provides new insights on translation regulation and the associated phenotypic impact in human cells, associated to CU. Discovery and functional assessment of a novel adipocyte population driven by intracellular Wnt/β-catenin signaling in mammals Wnt/{beta}-catenin signaling has been well established as a potent inhibitor of adipogenesis. Here, we identified a population of adipocytes that exhibit persistent activity of Wnt/{beta}-catenin signaling, as revealed by the Tcf/Lef-Gfp reporter allele, in embryonic and adult mouse fat depots, named as Wnt+ adipocytes. We showed that the {beta}-catenin-mediated signaling activation in these cells is Wnt ligand- and receptor-independent but relies on AKT/mTOR pathway and is essential for cell survival. Such adipocytes are distinct from classical ones in transcriptomic and genomic signatures and can be induced from various sources of mesenchymal stromal cells including human cells. Genetic lineage-tracing and targeted cell ablation studies revealed that these adipocytes convert into beige adipocytes directly and are also required for beige fat recruitment under thermal challenge, demonstrating both cell autonomous and non-cell autonomous roles in adaptive thermogenesis. Furthermore, mice bearing targeted ablation of these adipocytes exhibited glucose intolerance, while mice receiving exogenously supplied such cells manifested enhanced glucose utilization. Our studies uncover a unique adipocyte population in regulating beiging in adipose tissues and systemic glucose homeostasis. Source-sink connectivity: A novel interictal EEG marker for seizure localization Over 15 million epilepsy patients worldwide have drug-resistant epilepsy (DRE). Successful surgery is a standard of care treatment for DRE but can only be achieved through complete resection or disconnection of the epileptogenic zone (EZ), the brain region(s) where seizures originate. Surgical success rates vary between 20-80% because no clinically validated biological markers of the EZ exist. Localizing the EZ is a costly and time-consuming process beginning with non-invasive neuroimaging and often followed by days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity (e.g., low-voltage high frequency activity) on individual channels occurring immediately before seizures or spikes that occur on interictal iEEG (i.e., between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in EZ localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients.

Intracranial EEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aim to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the EZ. We hypothesize that when a patient is not clinically seizing, it is because the EZ is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, patient-specific dynamical network models (DNMs) were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics (SSMs). We validated the SSMs in a retrospective analysis of 65 patients by using the SSMs of the annotated EZ to predict surgical outcomes. The SSMs predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians predictions (surgical success rate of this dataset). In failed outcomes, we identified regions of the brain with high SSMs that were untreated. When compared to high frequency oscillations, the most commonly proposed interictal iEEG feature for EZ localization, SSMs outperformed in predictive power (by a factor of 1.2) suggesting SSMs may be an interictal iEEG fingerprint of the EZ. A Drug-free, Self-destruction Strategy to Combat Bacterial Infections by Using the Intrinsically formed Magnetic Nanoparticles in Bacterial Pathogens The growing number of multiple drug resistant (MDR) bacteria and the dwindling pipeline of new antibiotics are driving us towards a  post-antibiotic era in which even common infections would become difficult to treat. To address this, an antibiotic-free strategy that can combat multiple bacteria is recommended. Most of the proposed approaches nevertheless have several limitations, including bacterial targeting. To overcome such limitations, the proposed strategy employs the bacterial machinery to self-destruct. Herein, the biosynthesis of magnetic nanoparticle (MNP) is reported for the first time in multiple pathogenic bacteria, including MDR bacteria. The intracellular MNPs composed of superparamagnetic zinc ferrites were formed in presence of iron and zinc precursors. Exposure of the treated bacteria/biofilms to an alternating magnetic field (AMF) exhibited hyperthermia (5-6{degrees}C) and a dramatic decrease in bacterial viability, suggesting the MNPs therapeutic potential. Likewise, the bacteria existing in vivo biosynthesize the MNPs by mining these elements from the host. To determine its therapeutic efficacy, the infected tissues were exposed directly to AMF. A 3-4 log reduction in bacterial burden, as compared to antibiotics treatment, confirmed the significance of using naturally existing MNPs to combat bacterial infections. The proposed broad-spectrum approach can therefore aid in overcoming the challenges facing anti-bacterial therapies. BRPF3 knockdown or inhibition moderately reverses olaparib resistance in high grade serous ovarian carcinoma BackgroundPARP inhibitors (PARPi) kill cancer cells by stalling DNA replication and preventing DNA repair, resulting in a critical accumulation of DNA damage. Resistance to PARPi is a growing clinical problem in the treatment of high grade serous ovarian carcinoma (HGSOC). Acetylation of histone H3 lysine 14 (H3K14ac) and associated histone acetyltransferases (HATs) have known functions in DNA repair and replication, but their expression and activities have not been examined in the context of PARPi-resistant HGSOC.

ResultsUsing mass spectrometry profiling of histone modifications, we observed altered H3K14ac enrichment in PARPi-resistant HGSOC cells relative to isogenic PARPi-sensitive lines. By RT-qPCR and RNA-Seq, we also observed altered expression of numerous HATs in PARPi-resistant HGSOC cells and a PARPi-resistant PDX model. Knockdown of HATs only modestly altered PARPi response, although knockdown and inhibition of PCAF significantly increased resistance. Pharmacologic inhibition of HBO1 severely depleted H3K14ac but did not affect PARPi response. However, knockdown and inhibition of BRPF3, which is known to interact in a complex with HBO1, did reduce PARPi resistance.

ConclusionsThis study demonstrates that severe depletion of H3K14ac does not affect PARPi response in HGSOC. Our data suggest that bromodomain functions of HAT proteins such as PCAF, or accessory proteins such as BRPF3, may play a greater role in PARPi response than acetyltransferase functions. LazySampling and LinearSampling: Fast Stochastic Sampling of RNA Secondary Structure with Applications to SARS-CoV-2 Many RNAs fold into multiple structures at equilibrium. The classical stochastic sampling algorithm can sample secondary structures according to their probabilities in the Boltzmann ensemble, and is widely used. However, this algorithm, consisting of a bottom-up partition function phase followed by a top-down sampling phase, suffers from three limitations: (a) the formulation and implementation of the sampling phase are unnecessarily complicated; (b) the sampling phase repeatedly recalculates many redundant recursions already done during the partition function phase; (c) the partition function runtime scales cubically with the sequence length. These issues prevent stochastic sampling from being used for very long RNAs such as the full genomes of SARS-CoV-2. To address these problems, we first adopt a hypergraph framework under which the sampling algorithm can be greatly simplified. We then present three sampling algorithms under this framework, among which the LazySampling algorithm is the fastest by eliminating redundant work in the sampling phase via on-demand caching. Based on LazySampling, we further replace the cubic-time partition function by a linear-time approximate one, and derive LinearSampling, an end-to-end linear-time sampling algorithm that is orders of magnitude faster than the standard one. For instance, LinearSampling is 176x faster (38.9s vs. 1.9h) than Vienna RNAsubopt on the full genome of Ebola virus (18,959 nt). More importantly, LinearSampling is the first RNA structure sampling algorithm to scale up to the full-genome of SARS-CoV-2 without local window constraints, taking only 69.2 seconds on its reference sequence (29,903 nt). The resulting sample correlates well with the experimentally-guided structures. On the SARS-CoV-2 genome, LinearSampling finds 23 regions of 15 nt with high accessibilities, which are potential targets for COVID-19 diagnostics and drug design.

See code: https://github.com/LinearFold/LinearSampling Deep inference of seabird dives from GPS-only records: performance and generalization properties AO_SCPLOWBSTRACTC_SCPLOWAt-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as  fine-tuning. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation. To make easier such applications, we share online the different models we trained on the considered datasets (https://github.com/AmedeeRoy/BirdDL/models).

Author SummaryOver the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as  ready-to-use tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training. The initial response of females towards congeneric males matches the propensity to hybridise in Ophthalmotilapia. AO_SCPLOWBSTRACTC_SCPLOWCichlid radiations often harbour closely related species with overlapping niches and distribution ranges. Such species sometimes hybridise in nature, which raises the question how can they coexist. This also holds for the Tanganyika mouthbrooders Ophthalmotilapia ventralis and O. nasuta. Earlier studies found indications of asymmetrical hybridisation with females of O. ventralis accepting males of O. nasuta, but not the other way around. We hypothesised that this was due to differences in the capacity for species recognition. Given the higher propensity of O. ventralis females towards hybridisation, we expect a reduced ability for species recognition in O. ventralis females, compared to O. nasuta females. We staged two experiments, one focusing on 22 female O. nasuta and one on 21 female O. ventralis. These fish were placed in one half of a tank and briefly exposed to a conspecific or a heterospecific male, a conspecific female, or nothing (control). Female response was evaluated by scoring six tracking parameters and by noting the occurrence of ten discrete behaviours before and during the encounter. Females always responded to the presence of another fish by approaching it. Remarkably, for both O. nasuta and O. ventralis, we did not find a different response between encounters with conspecific males and females. However, in agreement with our hypothesis, O. nasuta females behaved differently towards conspecific or heterospecific males, whereas O. ventralis females did not. When presented with a heterospecific male, O. nasuta females performed a lower number of  ram behaviours. Additionally, they never displayed the  flee behaviour, a component of the species mating repertoire that was seen in all but one of the presentations with a conspecific male. Our findings show that differences in species recognition at first encounter predict to a large degree the outcome of the mating process, even in the absence of mating behaviour. Genomic regions associate with major axes of variation driven by gas exchange and leaf construction traits in cultivated sunflower (Helianthus annuus L.) Stomata and leaf veins play an essential role in transpiration and the movement of water throughout leaves. These traits are thus thought to play a key role in the adaptation of plants to drought and a better understanding of the genetic basis of their variation and coordination could inform efforts to improve drought tolerance. Here, we explore patterns of variation and covariation in leaf anatomical traits and analyze their genetic architecture via genome-wide association (GWA) analyses in cultivated sunflower (Helianthus annuus L.). Traits related to stomatal density and morphology as well as lower order veins were manually measured from digital images while the density of minor veins was estimated using a novel deep learning approach. Leaf, stomatal, and vein traits exhibited numerous significant correlations that generally followed expectations based on functional relationships. Correlated suites of traits could further be separated along three major principal component (PC) axes that were heavily influenced by variation in traits related to gas exchange, leaf hydraulics, and leaf construction. While there was limited evidence of colocalization when individual traits were subjected to GWA analyses, major multivariate PC axes that were most strongly influenced by several traits related to gas exchange or leaf construction did exhibit significant genomic associations. These results provide insight into the genetic basis of leaf trait covariation and showcase potential targets for future efforts aimed at modifying leaf anatomical traits in sunflower.

Significance StatementUsing traditional and automated/high-throughput (using a novel deep learning approach) phenotyping methods we studied leaf anatomical variation in sunflower. Genome-wide association (GWA) analyses identified numerous genomic regions underlying individual trait variation and regions underlying major multivariate axes of phenotypic variation. These results illustrate the value of employing a multivariate approach to GWA analyses and shed light on the extent to which leaf trait (co-)variation can be genetically decoupled to explore novel phenotypic space. BRD2 inhibition blocks SARS-CoV-2 infection by reducing transcription of the host cell receptor ACE2 SARS-CoV-2 infection of human cells is initiated by the binding of the viral Spike protein to its cell-surface receptor ACE2. We conducted a targeted CRISPRi screen to uncover druggable pathways controlling Spike protein binding to human cells. We found that the protein BRD2 is required for ACE2 transcription in human lung epithelial cells and cardiomyocytes, and BRD2 inhibitors currently evaluated in clinical trials potently block endogenous ACE2 expression and SARS-CoV-2 infection of human cells, including those of human nasal epithelia. Moreover, pharmacological BRD2 inhibition with the drug ABBV-744 inhibited SARS-CoV-2 replication in Syrian hamsters. We also found that BRD2 controls transcription of several other genes induced upon SARS-CoV-2 infection, including the interferon response, which in turn regulates the antiviral response. Together, our results pinpoint BRD2 as a potent and essential regulator of the host response to SARS-CoV-2 infection and highlight the potential of BRD2 as a novel therapeutic target for COVID-19. Patterned apoptosis has an instructive role for local growth and tissue shape in a fast-growing epithelium What regulates organ size and shape remains one of the fundamental mysteries of modern biology. So far, research in this area has primarily focused on deciphering the regulation in time and space of growth and cell division, while the contribution of cell death has been much more neglected. This includes studies of the Drosophila wing imaginal disc, the prospective fly wing which undergoes massive growth during larval stage, and represents one of the best characterised systems for the study of growth and patterning. So far, it has been assumed that cell death was relatively neglectable in this tissue and as a result the pattern of growth was usually attributed to the distribution of cell division. Here, using systematic mapping and registration combined with quantitative assessment of clone size and disappearance, we show for the first time that cell death is not neglectable, and outline a persistent pattern of cell death and clone elimination in the disc. Local variation of cell death is associated with local variation of clone size, pointing to an impact of cell death on local growth which is not fully compensated by proliferation. Using morphometric analyses of adult wing shape and genetic perturbations, we provide evidence that patterned death affects locally and globally adult wing shape and size. This study describes a roadmap for accurate assessment of the contribution of cell death to tissue shape, and outlines for the first time an important instructive role of cell death in modulating quantitatively local growth and the morphogenesis of a fast-growing tissue. Weakly deleterious natural genetic variation greatly amplifies probability of resistance in multiplexed gene drive systems Evolution of resistance is a major barrier to successful deployment of gene drive systems to suppress natural populations, which could greatly reduce the burden of many vector borne diseases. Multiplexed guide RNAs that require resistance mutations in all target cut sites is a promising anti-resistance strategy, since in principle resistance would only arise in unrealistically large populations. Using novel stochastic simulations that accurately model evolution at very large population sizes, we explore the probability of resistance due to three important mechanisms: 1) non-homologous end-joining mutations, 2) single nucleotide mutants arising de novo or, 3) single nucleotide polymorphisms pre-existing as standing variation. Our results explore the relative importance of these mechanisms and highlight a complexity of the mutation-selection-drift balance between haplotypes with complete resistance and those with an incomplete number of resistant alleles. We find this leads to a qualitatively new phenomenon where weakly deleterious naturally occurring variants greatly amplify the probability of multi-site resistance. This challenges the intuition that many target sites would guarantee prevention of resistance, where in the face of standing genetic variation, it can be probable even in not very large populations. This result has broad application to resistance arising in many multi-site evolutionary scenarios including multi-drug resistance to antibiotics, antivirals and cancer treatments, as well as the evolution of vaccine escape mutations in large populations. 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. Inability to switch from ARID1A-BAF to ARID1B-BAF impairs exit from pluripotency and commitment towards neural crest formation in ARID1B-related neurodevelopmental disorders The BAF complex modulates chromatin accessibility. Specific BAF configurations have functional consequences, and subunit switches are essential for cell differentiation. ARID1B and its paralog ARID1A encode for mutually exclusive BAF subunits. De novo ARID1B haploinsufficient mutations cause a neurodevelopmental disorder spectrum, including Coffin-Siris syndrome, which is characterized by neurological and craniofacial features. Here, we reprogrammed ARID1B+/- Coffin-Siris patient-derived skin fibroblasts into iPSCs and modeled cranial neural crest cell (CNCC) formation. We discovered that ARID1B is active only during the first stage of this process, coinciding with neuroectoderm specification, where it is part of a lineage-specific BAF configuration (ARID1B-BAF), which includes SMARCA4 and nine additional subunits. ARID1B-BAF acts as a gatekeeper, ensuring exit from pluripotency and lineage commitment, by attenuating NANOG, SOX2 and thousands of enhancers directly regulated by these two pluripotency factors at the iPSC stage.

In iPSCs, these enhancers are maintained active by an ARID1A-containing BAF. At the onset of differentiation, cells transition from ARID1A-BAF to ARID1B-BAF, eliciting attenuation of the NANOG/SOX2 networks, and triggering pluripotency exit. Coffin-Siris patient cells fail to perform the ARID1A/ARID1B switch and maintain ARID1A-BAF at pluripotency enhancers throughout all stages of CNCC formation. This leads to a persistent and aberrant SOX2 and NANOG activity, which impairs CNCC formation. In fact, despite showing the typical neural crest signature (TFAP2A+, SOX9+), ARID1B-haploinsufficient CNCCs are also NANOG/OCT4-positive, in stark contrast with the ARID1B-wt CNCCs, which are NANOG/OCT4-negative.

These findings suggest a connection between ARID1B mutations, neuroectoderm formation, and a pathogenic mechanism for Coffin-Siris syndrome. Top-down generation of low-precision representations improves the perception and imagination of fine-scale visual information Predictive-coding perception or imagination requires top-down generated neural representations in the primary visual cortex (V1) to reconstruct or simulate the V1 representations bottom-up stimulated by the seen images. However, top-down generated representations have low coding precision in both perception and imagination tasks. Why and how does the brain use top-down generated low-precision representations to reconstruct or simulate bottom-up stimulated high-precision representations? How can information of fine spatial scale be perceived or imagined using the top-down generated low-precision representations? By modeling the visual system using variational auto-encoder, we reveal that training to generate low-precision representations facilitates high-order cortex to form representations smooth to shape morphing of stimuli. Fine-scale visual information, if sparse, can be more accurately and robustly perceived or creatively imagined by inferring from generated representations with low (instead of high) coding precision. Therefore, generating low-precision representations is not a shortcoming, but instead a strategy that the brain uses to improve the perception and imagination of fine-scale information. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI Unevolved proteins from modern and prebiotic amino acids manifest distinct structural profiles Natural proteins represent numerous but tiny structure/function islands in a vast ocean of possible protein sequences, most of which has not been explored by either biological evolution or research. Recent studies have suggested this uncharted sequence space possesses surprisingly high structural propensity, but development of an understanding of this phenomenon has been awaiting a systematic high-throughput approach.

Here, we designed, prepared, and characterized two combinatorial protein libraries consisting of randomized proteins, each 105 residues in length. The first library constructed proteins from the entire canonical alphabet of 20 amino acids. The second library used a subset of only 10 residues (A,S,D,G,L,I,P,T,E,V) that represent a consensus view of plausibly available amino acids through prebiotic chemistry. Our study shows that compact conformations resistant to proteolysis are (i) abundant (up to 40%) in random sequence space, (ii) independent of general Hsp70 chaperone system activity, and (iii) not granted solely by "late" and complex amino acid additions. The Hsp70 chaperone system effectively increases solubility and refoldability of the canonical alphabet but has only a minor impact on the "early" library. The early alphabet proteins are inherently more soluble and refoldable, possibly assisted by the cell-like environment in which these assays were performed.

Our work indicates that both early and modern amino acids are predisposed to supporting protein structure (either in forms of oligomers or globular/molten globule structures) and that protein structure may not be a unique outcome of evolution. Citation needed?Wikipedia bibliometrics during the first waveof 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. A human antibody reveals a conserved site on beta-coronavirus spike proteins and confers protection against SARS-CoV-2 infection Broadly neutralizing antibodies (bnAbs) to coronaviruses (CoVs) are valuable in their own right as prophylactic and therapeutic reagents to treat diverse CoVs and, importantly, as templates for rational pan-CoV vaccine design. We recently described a bnAb, CC40.8, from a coronavirus disease 2019 (COVID-19)-convalescent donor that exhibits broad reactivity with human beta-coronaviruses ({beta}-CoVs). Here, we showed that CC40.8 targets the conserved S2 stem-helix region of the coronavirus spike fusion machinery. We determined a crystal structure of CC40.8 Fab with a SARS-CoV-2 S2 stem-peptide at 1.6 [A] resolution and found that the peptide adopted a mainly helical structure. Conserved residues in {beta}-CoVs interacted with CC40.8 antibody, thereby providing a molecular basis for its broad reactivity. CC40.8 exhibited in vivo protective efficacy against SARS-CoV-2 challenge in two animal models. In both models, CC40.8-treated animals exhibited less weight loss and reduced lung viral titers compared to controls. Furthermore, we noted CC40.8-like bnAbs are relatively rare in human COVID-19 infection and therefore their elicitation may require rational structure-based vaccine design strategies. Overall, our study describes a target on {beta}-CoV spike proteins for protective antibodies that may facilitate the development of pan-{beta}-CoV vaccines.

SUMMARYA human mAb isolated from a COVID-19 donor defines a protective cross-neutralizing epitope for pan-{beta}-CoV vaccine design strategies Natural variations in reproductive timing of brood size and X-chromosome nondisjunction in Caenorhabditis elegans Reproductive timing underlies self-sperm production and X-chromosome nondisjunction rate in Caenorhabditis elegans. These traits can be measured as brood size and male-production rate, and brood size decreases and male-production rate increases as worms age. These phenotypic changes occur simultaneously; however, whether these changes share common underlying genetic architectures still remains unclear. To enhance our understanding of reproductive timing in C. elegans, we measured and compared these two reproductive timing-related traits of 96 wild strains during early, late and total reproductive periods. We found that the two traits exhibited natural phenotypic variation with few outliers and a similar reproductive timing pattern as previous reports. The brood size and the male-production rate were not genetically correlated, implying that they might have different genetic architectures and that meiosis quality can be maintained despite increased progeny-production in the late reproductive period caused by more self-sperm. We also identified loci and candidate genetic variants significantly associated with male-production rate in the late and total reproductive periods. Our results provide an insight into life history traits in wild C. elegans strains. The pH Dependence of Niclosamide Solubility, Dissolution, and Morphology Motivates Potentially Universal Mucin-Penetrating Nasal and Throat Sprays for COVID19, its Contagious Variants, and Other Respiratory Viral Infections MotivationWith the coronavirus pandemic still raging, prophylactic nasal and early treatment throat sprays could help prevent infection and reduce viral load. Niclosamide has the potential to treat a broad range of viral infections if local bioavailability is optimized as mucin-penetrating solutions as opposed to more traditional microparticle-based sprays that cannot penetrate the mucin.

ExperimentalpH-dependence of supernatant concentrations and dissolution rates of niclosamide were measured in buffered solutions by Nanodrop-UV/Vis-spectroscopy for niclosamide from different suppliers, as precipitated material, and as cosolvates. Data was compared to predictions from Henderson Hasselbalch and precipitation pH models. Optimal microscopy was used to observe the morphologies of precipitated and converted niclosamide.

ResultsSupernatant-concentrations of niclosamide increased with increasing pH, from 1.77uM at pH 3.66 to 30uM at pH 8, and more rapidly from 90uM at pH8.5 to 300uM at pH 9.1, reaching 641uM at pH 9.5. Logarithmic rates for dissolution increased by [~]3x for pHs 8.62 to 9.44. However, when precipitated from supersaturated solution, niclosamide equilibrated to much lower final supernatant concentrations, reflective of more stable polymorphs at each pH that were also apparent for niclosamide from other suppliers and cosolvates.

ConclusionsGiven niclosamides activity against COVID19, its more contagious variants, and other respiratory viral infections, these niclosamide solutions, that put the virus in lockdown, could represent universal prophylactic nasal and early treatment throat sprays. As solutions they would be the simplest and potentially most effective formulations from both an efficacy standpoint as well as manufacturing and distribution, with no cold chain. They now just need testing.