'rbioacc': an R-package to analyse toxicokinetic data O_LI rbioacc is an  R-package dedicated to the analysis of experimental data collected from bioaccumulation tests during which organisms are exposed to a chemical (exposure phase) and then put into a clean media (depuration phase). Internal concentrations are regularly measured over time all along the experiment.
C_LIO_LI rbioacc provides ready-to-use functions to visualize and fully analyze such data. Under a Bayesian framework, this package fits a generic one-compartment toxicokinetic (TK) model automatically built from the data. It provides TK parameter estimates (appropriate uptake and elimination rates) and bioaccumulation metrics (e.g., BCF, BSAF, BMF). All parameter estimates, bioaccumulation metrics as well as predictions of internal concentrations into organisms are delivered with their uncertainty.
C_LIO_LIBioaccumulation metrics are primarily provided in support of environmental risk assessment, in full compliance with regulatory requirements required to approve marketing applications of chemical substances.
C_LIO_LIThis paper gives brief worked examples of the use of  rbioacc from data collected through standard bioaccumulation tests, and publicly available within the scientific literature. These examples constitute step-by-step user-guides to analyze any new data set, uploaded in the right format.
C_LI
Symbiodiniaceae conduct under natural bleaching stress during advanced gametogenesis stages of a mesophotic coral The mesophotic coral Alveopora allingi from the northern Gulf of Eilat/Aqaba, Red Sea, is affected by year-round partial coral-bleaching events. During these events, the migration of Symbiodiniaceae takes place from the coral-host mesoglea to the developed oocytes in bleached parts of colonies of A. allingi but not in the non-bleached parts. Additionally, these oocytes are abnormal, missing part of the structural material of the peripheral areas and are also significantly larger in the bleached areas of the colonies. Hence, we suggest a parasitic behavior of the symbionts or a commensalism relationship which enhance symbionts needs during bleaching periods and may boost the gametogenesis development in these corals. We propose that evolutionarily, this behavior may greatly contribute to the symbiont community survival throughout the bleaching period, and it can also be beneficial for the hosts persistence and adaptation to bleaching through the acquisition of a specific symbiont community following the bleaching event.
Kinetoplastid-specific X2-family kinesins interact with a kinesin-like pleckstrin homology domain protein that localizes to the trypanosomal microtubule quartet Kinesins are motor proteins found in all eukaryotic lineages that move along microtubules to mediate cellular processes such as mitosis and intracellular transport. In trypanosomatids, the kinesin superfamily has undergone a prominent expansion, resulting in one of the most diverse kinesin repertoires that includes the two kinetoplastid-restricted families X1 and X2. Here, we characterize in Trypanosoma brucei TbKifX2A, an orphaned X2 kinesin. TbKifX2A tightly interacts with TbPH1, a kinesin-like protein with a likely inactive motor domain, a rarely reported occurrence. Both TbKifX2A and TbPH1 localize to the microtubule quartet (MtQ), a characteristic but poorly understood cytoskeletal structure that wraps around the flagellar pocket as it extends to the cell body anterior. The proximal proteome of TbPH1 revealed two other interacting proteins, the flagellar pocket protein FP45 and intriguingly another X2 kinesin, TbKifX2C. Simultaneous ablation of TbKifX2A/TbPH1 results in the depletion of FP45 and TbKifX2C and also an expansion of the flagellar pocket, among other morphological defects. TbKifX2A is the first motor protein to be localized to the MtQ. The observation that TbKifX2C also associates with the MtQ suggests that the X2 kinesin family may have co-evolved with the MtQ, both kinetoplastid-specific traits. Classification, Using Field Potential Images, of Pacemaker Micro-coordination in the Mouse Intestine The flexible and sophisticated movement of the gastrointestinal (GI) tract implies the involvement of mechanisms other than enteric neural circuits, to coordinate excitation in microregions. We thus performed microimaging of pacemaker dynamics in the small intestine of mice since it contains typical network-forming pacemaker cells. A dialysis membrane-reinforced low-impedance microelectrode array (MEA) enabled field potentials over a wide frequency range to be stably measured in microregions. The pacemaker dynamics were classified into basic patterns despite large variations. In the developmental process, pacemaker activity was categorized as either an  expanding or a  migrating pattern that was initiated in or propagated to the MEA sensing area, respectively. The intercellular current of the volume conductor complicated the waveform of both activities. The existence of  expanding and  migrating patterns was attributable to duplicated pacemaker systems such as intracellular Ca2+ oscillation-activated and voltage-gated mechanisms. Additionally, from the spatio-temporal feature during the period of pacemaker events, the  bumpy/aberrant pattern was defined by aberrant, incoherent propagation, and associated with local impairment of excitability, while the  colliding/converging pattern involved the interaction of multiple activities in the MEA area. Interconversion between the four micro-coordination patterns occurred in the same microregion. 5-Hydroxytryptamine (5-HT) promoted  migrating activity, implying an improvement or restoration of spatial conductivity. These results agree well with the action of 5-HT to change GI movement toward propulsion. In conclusion, our MEA method of microimaging classification enables the quantitative assessment of spatio-temporal electric coordination underlying GI motility, suggesting its application to small model animals. Microvesicles Transfer Mitochondria and Increase Mitochondrial Function in Brain Endothelial Cells We have demonstrated, for the first time that microvesicles, a sub-type of extracellular vesicles (EVs) derived from hCMEC/D3: a human brain endothelial cell (BEC) line transfer polarized mitochondria to recipient BECs in culture and to neurons in mice acute brain cortical and hippocampal slices. This mitochondrial transfer increased ATP levels by 100 to 200-fold (relative to untreated cells) in the recipient BECs exposed to oxygen-glucose deprivation, an in vitro model of cerebral ischemia. We have also demonstrated that transfer of microvesicles, the larger EV fraction, but not exosomes resulted in increased mitochondrial function in hypoxic endothelial cultures. Gene ontology and pathway enrichment analysis of EVs revealed a very high association to glycolysis-related processes. In comparison to heterotypic macrophage- derived EVs, BEC-derived EVs demonstrated a greater selectivity to transfer mitochondria and increase endothelial cell survival under ischemic conditions.

HighlightsO_LIMicrovesicles transfer mitochondria to endothelial cells and brain slice neurons
C_LIO_LIMitochondrial transfer increased ATP in ischemic brain endothelial cells (BECs)
C_LIO_LITransfer of microvesicles increased mitochondrial function in hypoxic BECs
C_LIO_LITransfer of exosomes did not affect mitochondrial function in hypoxic BECs
C_LIO_LIHomotypic BEC-derived EVs result in greater ATP levels in the recipient BECs
C_LI Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. A MALDI-TOF assay identifies nilotinib as an inhibitor of inflammation in acute myeloid leukaemia Inflammatory responses are important in cancer, particularly in the context of monocyte-rich aggressive myeloid neoplasm. We developed a label-free cellular phenotypic drug discovery assay to identify anti-inflammatory drugs in human monocytes derived from acute myeloid leukaemia (AML), by tracking several biological features ionizing from only 2,500 cells using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. A proof-of-concept screen showed that the BCR-ABL inhibitor nilotinib, but not the structurally similar imatinib, blocks inflammatory responses. In order to identify the cellular (off-)targets of nilotinib, we performed thermal proteome profiling (TPP). Unlike imatinib, nilotinib and other later generation BCR-ABL inhibitors inhibit the p38-MK2/3 signalling axis which suppressed the expression of inflammatory cytokines, cell adhesion and innate immunity markers in activated human monocytes derived from AML. Thus, our study provides a tool for the discovery of new anti-inflammatory drugs, which could contribute to the treatment of inflammation in myeloid neoplasms and other diseases.

Key PointsLabel-free cell-based assay identifies new anti-inflammatory drugs using MALDI-TOF MS. Nilotinib reduces inflammation by inhibition of MAPK14-MK2/3 signalling axis in AML. Observation of non-dormant persister cells reveals diverse modes of survival in antibiotic persistence Bacterial persistence is a phenomenon in which a small fraction of isogenic bacterial cells survives a lethal dose of antibiotics. It is generally assumed that persistence is caused by cells with inactive growth generated prior to drug exposure. However, evidence from direct observation is scarce due to the extremely low frequencies of persisters. Here, we visualize the responses of more than 106 individual cells of wildtype Escherichia coli to lethal doses of antibiotics, sampling cells from different growth phases and culture media. We show that preexisting growth-arrested dormant persisters constitute only minor fractions of persistent cell lineages in populations sampled from exponential phase. Non-dormant persisters survive with radical morphological changes in response to drug exposure, including L-form-like morphologies or filamentation. Incubating cells under stationary phase conditions increases both the frequency and the probability of survival of dormant cells. While dormant cells in late stationary phase express a general stress response regulator, RpoS, at high levels, persistent cell lineages show lower levels of RpoS among the dormant cells. These results demonstrate that diverse survival pathways coexist within bacterial populations to achieve persistence and that persistence does not necessarily require dormant cells. Structural basis for Nirmatrelvir in vitro efficacy against SARS-CoV-2 variants The COVID-19 pandemic continues to be a public health threat with emerging variants of SARS-CoV-2. Nirmatrelvir (PF-07321332) is a reversible, covalent inhibitor targeting the main protease (Mpro) of SARS-CoV-2 and the active protease inhibitor in PAXLOVID (nirmatrelvir tablets and ritonavir tablets). We evaluated the in vitro catalytic activity and in vitro potency of nirmatrelvir against the main protease (Mpro) of prevalent variants of concern (VOC) or variants of interest (VOI): Alpha (, B.1.1.7), Beta ({beta}, B.1.351), Delta ({delta}, B1.617.2), Gamma ({gamma}, P.1), Lambda ({lambda}, B.1.1.1.37/C37), Omicron (o, B.1.1.529) as well as the original Washington or wildtype strain. These VOC/VOI carry prevalent mutations at varying frequencies in the Mpro specifically for: , {beta},{gamma} (K90R), {lambda} (G15S) and o (P132H). In vitro biochemical enzymatic assay characterization of the enzyme kinetics of the mutant Mpros demonstrate that they are catalytically comparable to wildtype. Nirmatrelvir has similar potency against each mutant Mpro including P132H that is observed in the Omicron variant with a Ki of 0.635 nM as compared to a Ki of 0.933nM for wildtype. The molecular basis for these observations were provided by solution-phase structural dynamics and structural determination of nirmatrelvir bound to the o, {lambda} and {beta} Mpro at 1.63 - 2.09 [A] resolution. These in vitro data suggest that PAXLOVID has the potential to maintain plasma concentrations of nirmatrelvir many-fold times higher than the amount required to stop the SARS-CoV-2 VOC/VOI, including Omicron, from replicating in cells (1). Cell type-specific differential expression in spatial transcriptomics Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed (DE) within specific cell types across tissue context. We show that current approaches cannot learn cell type-specific DE due to changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type. Here, we introduce a statistical method, Cell type-Specific Inference of Differential Expression (C-SIDE), that identifies cell type-specific patterns of differential gene expression while accounting for localization of other cell types. We model spatial transcriptomics gene expression as an additive mixture across cell types of general log-linear cell type-specific expression functions. This approach provides a unified framework for defining and identifying gene expression changes in a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MER-FISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimers mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our C-SIDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

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

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Propionate ameliorates diabetes-induced neurological dysfunction through regulating the PI3K/Akt/eNOS signaling pathway A large body of research has established diabetes-related cognitive deterioration, sometimes known as "diabetic encephalopathy." Current evidence supports that oxidative stress, neuronal apoptosis, and cerebral microcirculation weakness are associated with cognition deficits induced by diabetes. The present study explores the effect of propionate on neurological deficits, cerebral blood flow, and oxidative stress in diabetic mice. Propionate can markedly improve neurological function, which is correlated with its capabilities of stimulating nitric oxide (NO) production, increasing cerebral microcirculation, suppressing oxidative stress and reducing neuron loss in the hippocampus. In addition, the results of Western Blotting indicated that the brain-protective function of propionate in streptozocin (STZ)-induced insulin-dependent diabetes mellitus (IDDM) mice is related to phosphoinositide 3-kinase (PI3K)/serine-threonine protein kinase (Akt)/endothelial nitric oxide synthase(eNOS) signaling pathway. In a diabetic mouse model, propionate reduces cerebral microcirculation, hippocampus apoptosis, and neurological impairment. Thus, propionate, now employed as a food preservative, may also help slow diabetes-induced cognitive loss.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/464493v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@81fa09org.highwire.dtl.DTLVardef@1469451org.highwire.dtl.DTLVardef@b37fa1org.highwire.dtl.DTLVardef@8037e7_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIPropionate ameliorates diabetic-induced depression-like behavior, spatial learning and memory deficits.
C_LIO_LIPropionate increases cerebral microcirculation by enhancing NO production in diabetic mice.
C_LIO_LIPropionate suppresses oxidative stress and reduces neuron loss in the hippocampus.
C_LIO_LIThe brain-protective function of propionate is related to PI3K/Akt/eNOS signaling pathway.
C_LI The SLIM1 transcription factor is required for arsenic resistance in Arabidopsis thaliana The transcriptional regulators of arsenic-induced gene expression remain largely unknown. Sulfur assimilation is tightly linked with arsenic detoxification. Here we report that mutant alleles in the SLIM1 transcription factor are substantially more sensitive to arsenic than cadmium. Arsenic treatment caused high levels of oxidative stress in the slim1 mutants, and slim1 alleles were impaired in both thiol and sulfate accumulation. We further found enhanced arsenic accumulation in roots of slim1 mutants. Transcriptome analyses indicate an important role for SLIM1 in arsenic-induced tolerance mechanisms. The present study identifies the SLIM1 transcription factor as an essential component in arsenic tolerance and arsenic-induced gene expression. Our results suggest that the severe arsenic sensitivity of the slim1 mutants is caused by altered redox status. Comparison of mouse models reveals a molecular distinction between psychotic illness in PWS and schizophrenia Prader-Willi Syndrome (PWS) is a neurodevelopmental disorder caused by mutations affecting paternal chromosome 15q11-q13, and characterized by hypotonia, hyperphagia, impaired cognition and behavioural problems. Psychotic illness is a challenging problem for individuals with PWS and has different rates of prevalence in distinct PWS genotypes. Previously, we demonstrated behavioural and cognitive endophenotypes of relevance to psychiatric illness in a mouse model for one of the associated PWS genotypes, namely PWS-IC, in which deletion of the imprinting centre leads to loss of paternal imprinted gene expression and over-expression of Ube3a. Here we examine the broader gene expression changes that are specific to the psychiatric endophenotypes seen in this model. To do this we compared the brain transcriptomic profile of the PWS-IC mouse to the PWS-cr model that carries a deletion of the PWS minimal critical interval spanning the snoRNA Snord116 and Ipw. Firstly, we examined the same behavioural and cognitive endophenotypes of relevance to psychiatric illness in the PWS-cr mice. Unlike the PWS-IC mice, PWS-cr exhibit no differences in locomotor activity, sensory-motor gating, and attention. RNA-seq analysis of neonatal whole brain tissue revealed a greater number of transcriptional changes between PWS-IC and wild-type littermates, than between PWS-cr and wild-type littermates. Moreover, the differentially expressed genes in the PWS-IC brain were enriched for GWAS variants of episodes of psychotic illness but, interestingly, not schizophrenia. These data illustrate the molecular pathways that may underpin psychotic illness in PWS and have implication for potential therapeutic interventions. Peeling Back the Layers: First Phylogenomic Insights into the Ledebouriinae (Scilloideae, Asparagaceae) The Ledebouriinae (Scilloideae, Asparagaceae) are a widespread group of bulbous geophytes found predominantly throughout seasonal climates in sub-Saharan Africa, with a handful of taxa in Madagascar, the Middle East, India, and Sri Lanka. Phylogenetic relationships within the group have been historically difficult to elucidate. Here, we provide the first phylogenomic perspective into the Ledebouriinae. Using the Angiosperms353 targeted enrichment probe set, we consistently recovered four major clades (i.e., two Ledebouria clades, Drimiopsis, and Resnova). The two Ledebouria clades closely align with geography, either consisting almost entirely of sub-Saharan African taxa (Ledebouria Clade A), or East African and non-African taxa (Ledebouria Clade B). Our results suggest that the Ledebouriinae likely underwent a rapid radiation leading to rampant incomplete lineage sorting. We additionally find evidence for potential historical hybridization between Drimiopsis and a subclade within Ledebouria Clade A. Protein-protein docking with large-scale backbone flexibility using coarse-grained Monte-Carlo simulations Most of the protein-protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein-protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein-protein complexes, we obtained acceptable quality models for a significant number of cases. A terrain treadmill to study animal locomotion through large obstacles A major challenge to understanding locomotion in complex 3-D terrain with large obstacles is to create tools for controlled, systematic lab experiments. Existing terrain arenas only allow observations at small spatiotemporal scales ([~]10 body length, [~]10 stride cycles). Here, we create a terrain treadmill to enable high-resolution observations of animal locomotion through large obstacles over large spatiotemporal scales. An animal moves through modular obstacles on an inner sphere, while a rigidly-attached, concentric, transparent outer sphere rotated with the opposite velocity via closed-loop feedback to keep the animal on top. During sustained locomotion, a discoid cockroach moved through pillar obstacles for 25 minutes ({approx} 2500 strides) over 67 m ({approx} 1500 body lengths), and was contained within a radius of 4 cm (0.9 body length) for 83% of the duration, even at speeds of up to 10 body length/s. The treadmill enabled observation of diverse locomotor behaviors and quantification of animal-obstacle interaction.

Summary StatementA device keeps a small animal on top of a sphere while it traverses obstacles, creating a "terrain treadmill" to study locomotion over a long time and distance at high-resolution. Spatial organization of nuclear pores in Xenopus laevis oocytes Nuclear pores are protein assemblies inserted in the nuclear envelope of eukaryotic cells, acting as main gates for communication between nucleus and cytoplasm. So far, nuclear pores have been extensively studied to determine their structure and composition, yet their spatial organization and geometric arrangement on the nuclear surface are still poorly understood. Here, we analyze super-resolution images of the surface of Xenopus laevis oocyte nuclei during development, and characterize the arrangement of nuclear pores using tools commonly employed to study the atomic structural and topological features of soft matter. To interpret the experimental results, we hypothesize an effective interaction among nuclear pores and implemented it in extensive numerical simulations of octagonal clusters mimicking typical pore shapes. Thanks to our simple model, we find simulated spatial distributions of nuclear pores that are in excellent agreement with experiments, suggesting that an effective interaction among nuclear pores exists and could explain their geometrical arrangement. Furthermore, our results show that the statistical features of the geometric arrangement of nuclear pores do not depend on the type of pore-pore interaction, attractive or repulsive, but are mainly determined by the octagonal symmetry of each single pore. These results pave the way to further studies needed to determine the biological nature of pore-pore interactions. Beyond Spike: Identification of nine highly prevalent SARS-CoV-2-specific CD8 T-cell epitopes in a large Norwegian cohort T-cell epitopes with broad population coverage may form the basis for a new generation of SARS-CoV-2 vaccines. However, published studies on immunoprevalence are limited by small test cohorts, low frequencies of antigen-specific cells and lack of data correlating eluted HLA ligands with T-cell responsiveness. As the protective role of pre-existing cross-reactivity to homologous peptides is unclear, we aimed to identify SARS-CoV-2-specific minimal epitopes recognized by CD8 T-cells among 48 peptides eluted from prevalent HLA alleles, and an additional 84 predicted binders, in a large cohort of convalescents (n=83) and pre-pandemic control samples (n=19). We identified nine conserved SARS-CoV-2-specific epitopes restricted by four of the most prevalent HLA class I alleles in the Norwegian study cohort, to which responding CD8 T cells were detected in 70-100% of convalescents expressing the relevant HLA allele. Only two of these were derived from the Spike protein, included in current vaccines. We found a strong correlation between immunoprevalence and immunodominance. Thus, the CD8 T-cell response to SARS-CoV-2 is more focused than previously believed. Using a new algorithm, we predict that a vaccine including these epitopes could induce a T-cell response in 83% of Caucasians. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. Strength of interactions in the Notch gene regulatory network determines patterning and fate in the notochord Development of multicellular organisms requires the generation of gene expression patterns that determines cell fate and organ shape. Groups of genetic interactions known as Gene Regulatory Networks (GRNs) play a key role in the generation of such patterns. However, how the topology and parameters of GRNs determine patterning in vivo remains unclear due to the complexity of most experimental systems. To address this, we use the zebrafish notochord, an organ where coin-shaped precursor cells are initially arranged in a simple unidimensional geometry. These cells then differentiate into vacuolated and sheath cells. Using newly developed transgenic tools together with in vivo imaging, we identify jag1a and her6/her9 as the main components of a Notch GRN that generates a lateral inhibition pattern and determines cell fate. Making use of this experimental system and mathematical modeling we show that lateral inhibition patterning requires that ligand-receptor interactions are stronger within the same cell than in neighboring cells. Altogether, we establish the zebrafish notochord as an experimental system to study pattern generation, and identify and characterize how the properties of GRNs determine self-organization of gene patterning and cell fate. Visualizing functional human profilin in cells and in vitro applications Profilin is an essential regulator of actin and microtubule dynamics and therefore a critical control point for the normal division, motility, and morphology of cells. Most studies of profilin have focused on biochemical investigations using purified protein because high cellular concentrations present challenges for conventional imaging modalities. In addition, past studies that employed direct labeling or conventional fusion protein strategies compromised different facets of profilin function. We engineered two versions of tagged profilin that retain native activities with respect to phosphoinositide lipids, actin monomers, formin-mediated actin assembly, and microtubule polymerization. mApple-profilin-1 directly binds to dimers of tubulin (kD = 1.7 {micro}M) and the microtubule lattice (kD = 10 {micro}M) to stimulate microtubule assembly. In cells, Halo-tagged profilin-1 fully rescues profilin-1(-/-) cells from knockout-induced perturbations to cell shape, actin filament architecture, and microtubule arrays. In cells expressing Halo-profilin, we visualized a subset of individual molecules of profilin-1 by titrating fluorescent Halo-ligands. Further, we combined this imaging approach with specific function-disrupting point-mutants in profilin to visualize dynamic profilin associated with microtubules in live-cells. Thus, these tagged profilins are reliable tools for studying the dynamic interactions of profilin with actin or microtubules in live-cell or in vitro applications. Activation of the type 3 secretion system of enteropathogenic E. coli leads to remodeling of its membrane composition and function The cell envelope of gram-negative bacteria is a complex structure, essential for bacterial survival and for resistance to many antibiotics. Channels that cross the bacterial envelope and the host cell membrane form secretion systems that are activated upon attachment to host, enabling bacteria to inject effector molecules into the host cell, required for bacterial-host interaction. The type III secretion system (T3SS) is critical for the virulence of several pathogenic bacteria, including enteropathogenic E. coli (EPEC). The EPEC T3SS activation is associated with repression of carbon storage regulator (CsrA), resulting in gene expression remodeling, which is known to affect EPEC central carbon metabolism and contributes to the adaptation to a cell-adherent lifestyle in a poorly understood manner. We reasoned that the changes in bacterial envelope upon attachment to host and the activation of a secretion system may involve a modification of the lipid composition of bacterial envelope. Accordingly, we performed a lipidomics analysis on mutant strains that simulate T3SS activation. We saw a shift in glycerophospholipid metabolism towards the formation of lysophospholipids, attributed to corresponding upregulation of the phospholipase pldA and the acyltransferase ygiH upon T3SS activation in EPEC. We also detected a shift from menaquinones and ubiquinones to undecaprenyl lipids, concomitant to abnormal synthesis of O-antigen. The remodeling of lipid metabolism is mediated by CsrA and associated with increased bacteria cell size and Zeta potential, and a corresponding alteration in EPEC permeability to vancomycin, increasing the sensitivity of T3SS-activated strains and of adherent wild type EPEC to the antibiotic.

ImportanceThe characterization of EPEC membrane lipid metabolism upon attachment to host is an important step towards a better understanding the shift of EPEC, a notable human pathogen, from a planktonic to adherent life style. It may also apply to other pathogenic bacteria that use this secretion system. We predict that upon attachment to host cells the lipid remodeling upon T3SS activation contributes to bacterial fitness and promotes host colonization, and show that it is associated with increased cell permeability and higher sensitivity to vancomycin.

To the best of our knowledge, this is the first demonstration of a bacterial lipid remodeling due to activation of a secretion system. 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. 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. Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

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

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

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach.