A bioactive phlebovirus-like envelope protein in a hookworm endogenous retrovirus Endogenous retroviruses (ERVs), accounting for 14% of our genome, serve as a genetic reservoir from which new genes can emerge. Nematode ERVs are particularly diverse and informative of retrovirus evolution. We identify Atlas virus - a novel, intact ERV in the human hookworm Ancylostoma ceylanicum with an envelope protein genetically related to GN-GC glycoproteins from phleboviruses. A cryo-EM structure of Atlas GC reveals a class II viral membrane fusion protein fold not previously seen in retroviruses. Atlas GC has the structural hallmarks of an active fusogen. Atlas GC trimers insert into membranes with endosomal lipid compositions and low pH. When expressed on the plasma membrane, Atlas GC has cell-cell fusion activity. Atlas virus is transcriptionally active at specific stages of hookworm development. The preserved activities and expression pattern of Atlas GC suggest it has acquired a cellular function. Our work reveals an unexpected degree of structural and genetic plasticity in retroviruses.
N-VEGF, the autoregulatory arm of VEGF-A Vascular endothelial growth factor A (VEGF-A) is a secreted protein that stimulates angiogenesis in response to hypoxia. Under hypoxic conditions, a non-canonical long isoform called L-VEGF is concomitantly expressed with VEGF-A. Once translated, L-VEGF it is proteolytically cleaved to generate N-VEGF and VEGF-A. Interestingly, while VEGF-A is secreted and affects the surrounding cells, N-VEGF is mobilized to the nucleus. This suggests that N-VEGF participates in transcriptional response to hypoxia. In this study, we performed a series of complementary experiments to examine the functional role of N-VEGF. Strikingly, we found that the mere expression of N-VEGF followed by its hypoxia-independent mobilization to the nucleus was sufficient to induce key genes associated with angiogenesis, such as Hif1, VEGF-A isoforms, as well as genes associated with cell survival under hypoxia. Complementarily, when N-VEGF was genetically depleted, key hypoxia-induced genes were downregulated and cells were significantly susceptible to hypoxia-mediated apoptosis. This is the first reports of N-VEGF serving as an autoregulatory arm of VEGF-A. Further experiments will be needed to determine the role of N-VEGF in cancer and embryogenesis.
The activity and functions of soil microbial communities in the Finnish sub-Arctic vary across vegetation types Increased microbial activity in high-latitude soils due to climate change might lead to higher greenhouse gas (GHG) emissions. However, mechanisms of microbial GHG production and consumption in tundra soils are not thoroughly understood. We analyzed 116 soil metatranscriptomes from 73 sites in the Finnish sub-Arctic to investigate how the diversity and functional potential of bacterial and archaeal communities vary across vegetation types and soil layers. Soils differed in physicochemical conditions, with meadow soils being characterized by higher pH and low soil organic matter (SOM) and carbon/nitrogen ratio whereas dwarf shrub-dominated ecosystems with high SOM and low pH. Actinobacteria, Acidobacteria, Alphaproteobacteria, and Planctomycetes predominated all communities but there were significant differences on genus level between vegetation types, as plant polymer degrading groups were more active in shrub-dominated soils compared to meadows. Given that climate change scenarios predict expansion in dwarf shrubs at high latitudes, our results indicate that the rate of carbon turnover in tundra soils may increase in the future. Additionally, transcripts of methanotrophs were detected in the mineral layer of all soils, potentially moderating methane fluxes from deeper layers. In all, this study provides new insights into possible shifts in tundra microbial diversity and activity with climate change. 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. 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. Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2 Back and forth transmission of SARS-CoV-2 between humans and animals may lead to wild reservoirs of virus that can endanger efforts toward long-term control of COVID-19 in people, and protecting vulnerable animal populations that are particularly susceptible to lethal disease. Predicting high risk host species is key to targeting field surveillance and lab experiments that validate host zoonotic potential. A major bottleneck to predicting animal hosts is the small number of species with available molecular information about the structure of ACE2, a key cellular receptor required for viral cell entry. We overcome this bottleneck by combining species ecological and biological traits with 3D modeling of virus and host cell protein interactions using machine learning methods. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for over 5,000 mammals -- an order of magnitude more species than previously possible. The high accuracy predictions achieved by this approach are strongly corroborated by in vivo empirical studies. We identify numerous common mammal species whose predicted zoonotic capacity and close proximity to humans may further enhance the risk of spillover and spillback transmission of SARS-CoV-2. Our results reveal high priority areas of geographic overlap between global COVID-19 hotspots and potential new mammal hosts of SARS-CoV-2. With molecular sequence data available for only a small fraction of potential host species, predictive modeling integrating data across multiple biological scales offers a conceptual advance that may expand our predictive capacity for zoonotic viruses with similarly unknown and potentially broad host ranges. 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. New phylogenetic Markov models for inapplicable morphological characters This paper describes new Markov models for phylogenetic inference with inapplicable (anatomically dependent) morphological characters. It shows that the new solutions fall into two categories depending on the type of character hierarchy and require use of different Markov models. A combination of the new models and previous solutions is capable to model all general types of dependencies that may exists between morphological traits. The performance of the new models is assessed using theory and simulations. Bayesian phylogenetic inference with the new models and their construction for a hierarchy of custom complexity is demonstrated using RevBayes and the R package rphenoscate respectively. 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. Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease BackgroundStudies on DNA methylation (DNAm) in Alzheimers disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression.

MethodsHere, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n=337).

ResultsWe identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braaks tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in AD patients vs. controls.

ConclusionIn summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression. IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis through the MAPK Signaling Pathway AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets.

Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway.

ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS.

Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS. 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. Non-Newtonian Blood Rheology Impacts Left Atrial Stasis in Patient-Specific Simulations The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects can be subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered in calculating patient-specific blood stasis indices by computational fluid dynamics. Ribosome actuator via the SpoT/ppGpp pathway to mitigate gene overexpression burden Gene overexpression causes a burden on ribosomes, which decreases the expression of other genes and growth rate. Here, we engineer a genetic ribosome actuator that increases gene expression rate and growth rate by over 150% and 80%, respectively. The actuator expresses the hydrolysis domain of the SpoT enzyme (SpoTH) in a bacterial strain with high basal levels of ppGpp, thus increasing ribosome availability. We use this actuator in a feedforward control arrangement, wherein SpoTH is co-expressed with a gene of interest (GOI). Without SpoTH co-expression, activation of the GOI decreases the expression of a constitutive gene and growth rate by over 80% and 40%, respectively. By contrast, with SpoTH co-expression, the ribosome binding site (RBS) of SpoTH can be tuned to achieve inappreciable change of either the expression of the constitutive gene or growth rate when the GOI is activated to the same level. We finally employ the actuator to keep growth rate constant while expressing dCas9 to a level that would otherwise decrease growth rate by more than 40% due to toxicity. This actuator will be relevant in applications where high cellular protein concentrations are desired without growth defects or global reduction of gene expression. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. Library-free BoxCarDIA solves the missing value problem in label-free quantitative proteomics The last decade has seen significant advances in the application of quantitative mass spectrometry-based proteomics technologies to tackle important questions in plant biology. The current standard for quantitative proteomics in plants is the use of data-dependent acquisition (DDA) analysis with or without the use of chemical labels. However, the DDA approach preferentially measures higher abundant proteins, and often requires data imputation due to quantification inconsistency between samples. In this study we systematically benchmarked a recently developed library-free data-independent acquisition (directDIA) method against a state-of-the-art DDA label-free quantitative proteomics workflow for plants. We next developed a novel acquisition approach combining MS1-level BoxCar acquisition with MS2-level directDIA analysis that we call BoxCarDIA. DirectDIA achieves a 33% increase in protein quantification over traditional DDA, and BoxCarDIA a further 8%, without any changes in instrumentation, offline fractionation, or increases in mass-spectrometer acquisition time. BoxCarDIA, especially, offers wholly reproducible quantification of proteins between replicate injections, thereby addressing the long-standing missing-value problem in label-free quantitative proteomics. Further, we find that the gains in dynamic range sampling by directDIA and BoxCarDIA translate to deeper quantification of key, low abundant, functional protein classes (e.g., protein kinases and transcription factors) that are underrepresented in data acquired using DDA. We applied these methods to perform a quantitative proteomic comparison of dark and light grown Arabidopsis cell cultures, providing a critical resource for future plant interactome studies. Our results establish BoxCarDIA as the new method of choice in quantitative proteomics using Orbitrap-type mass-spectrometers, particularly for proteomes with large dynamic range such as that of plants. DCIS genomic signatures define biology and correlate with clinical outcome: a Human Tumor Atlas Network (HTAN) analysis of TBCRC 038 and RAHBT cohorts Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We made observations on DNA, RNA, and protein expression, and generated a de novo clustering scheme for DCIS that represents a fundamental transcriptomic organization at this early stage of breast neoplasia. Distinct stromal expression patterns and immune cell compositions were identified. We found RNA expression patterns that correlate with later events. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/448585v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@1755117org.highwire.dtl.DTLVardef@11ebdc0org.highwire.dtl.DTLVardef@13ba799org.highwire.dtl.DTLVardef@1784502_HPS_FORMAT_FIGEXP  M_FIG C_FIG HIGHLIGHTSO_LINew transcriptomic classification solution reveals 3 major subgroups in DCIS.
C_LIO_LIFour stroma-specific signatures identified.
C_LIO_LIutcome analysis identifies pathways involved in DCIS progression.
C_LIO_LICNAs characterize high risk of distant relapse IBC subtypes observed in DCIS.
C_LI Towards a unified model of naive T cell dynamics across the lifespan Naive CD4 and CD8 T cells are cornerstones of adaptive immunity, but the dynamics of their establishment early in life and how their kinetics change as they mature following release from the thymus are poorly understood. Further, due to the diverse signals implicated in naive T cell survival, it has been a long-held and conceptually attractive view that they are sustained by active homeostatic control as thymic activity wanes. Here we employ multiple experimental systems to identify a unified model of naive CD4 and CD8 T cell population dynamics across the mouse lifespan. We infer that both subsets divide rarely and progressively increase their survival capacity with cell age. Strikingly, this simple model captures naive CD4 T cell dynamics throughout life. In contrast, we find that newly generated naive CD8 T cells are lost more rapidly during the first 3-4 weeks of life, likely due to increased recruitment into memory. We find no evidence for elevated division rates in neonates, or for feedback regulation of naive T cell numbers at any age. We show how confronting mathematical models with diverse datasets can reveal a quantitative and remarkably simple picture of naive T cell dynamics from birth into old age. Dynamic interaction of BcsD subunit in type I bacterial cellulose synthase Cellulose is a promising biological material for supporting sustainable human life. This natural polymer is synthesized by cellulose synthase, a protein complex in the cell membrane. Cellulose synthase in bacteria is a hetero-subunit complex, and its subunit organization varies widely depending on the species. In the type I bacterial cellulose synthase complex, the BcsD (bacterial cellulose synthase D) protein is believed to play an important role in producing cellulose with long slender fiber morphology and high crystallinity, given the phenotype of the bcsD-deficient mutant and the specific existence of the type I operon in bacterial species synthesizing crystalline cellulose microfibrils such as Acetobacter. In this study, we successfully established a heterogeneously expressed Bcs protein in Escherichia coli as an experimental model and conducted biochemical studies for the BcsD protein and the other three major subunits of bacterial cellulose synthase, BcsA, BcsB, and BcsC. It has been shown that the BcsD protein interacts with the functionally required minimal subunits of the BcsAB complex, as well as the BcsC protein. Furthermore, it was shown that BcsD interacts with the BcsAB complex in two modes: direct protein-protein interactions and indirect interactions through the product cellulose. The former and latter modes represent the basal and active states of the type I bacterial cellulose synthase, respectively. This dynamic behavior of the BcsD protein is important for the type I bacterial cellulose synthase complex to regulate the crystallization process of cellulose. Noradrenergic control of non-REM sleep substates One promising approach towards understanding what makes sleep vulnerable in disease is to look at how wake-promoting mechanisms affect healthy sleep. Wake-promoting neuronal activity is inhibited during non-REM sleep (NREMS). However, many mammalian species, including humans, show recurrent moments of sleep fragility during which sensory reactivity is elevated. Wake-related neuronal activity could thus remain active in NREMS, but its roles in dynamic variations of sensory reactivity remain unknown. Here, we demonstrate that mouse NREMS is a brain state with recurrent fluctuations of the wake-promoting neurotransmitter noradrenaline on the [~]50-seconds time-scale. These fluctuations occurred around mean noradrenaline levels greater than the ones of quiet wakefulness, while they declined steeply in REMS. They coincided with a clustering of sleep spindle rhythms in the forebrain and with heart rate variations. We addressed the origins of these fluctuations by using closed-loop optogenetic locus coeruleus (LC) activation or inhibition timed to moments of low and high spindle activity during NREMS. We could suppress, lock or entrain sleep spindle clustering or heart rate variations, demonstrating that both fore- and hindbrain-projecting LC neurons show synchronized infraslow activity variations in natural NREMS. Noradrenergic modulation of thalamic but not cortical circuits was required for sleep spindle clustering and involved noradrenaline release into primary sensory and reticular thalamic nuclei that activated both 1- and {beta}-adrenergic receptors to cause slowly decaying membrane depolarizations. Noradrenergic signaling by LC, primarily known for attention promotion in wakefulness, renders mammalian NREMS more  wake-like on the close-to-minute-time scale through sustaining thalamocortical and autonomic sensory arousability. Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification Identification of peptides in mass spectrometry-based proteomics typically relies on spectra matches. As MS/MS spectra record presence and intensity of fragment ions, the match should take both fragment presence similarity and intensity similarity into consideration. Fragment presence similarity can be calculated with the help of fragment presence prediction such as theoretical enumeration of all possible fragment ions or selecting non-zero intensity ions from the result of fragment intensity prediction, but neither of these two methods is accurate enough. In this work, we developed a deep neural network based model, Alpha-Frag, to predict precisely the fragment ions that should be present for a given peptide. Alpha-Frag modelled fragment presence prediction as a multi-label classification task and trained with ProteomeTools dataset. In terms of intersection over union (IoU), Alpha-Frag achieved an average of >0.7 and outperformed the benchmarks across the validation datasets. Furthermore, fragment presence similarity was calculated based on presence prediction and incorporated into the peptide statistical validation tools as an additional score to improve peptide identifications. Our preliminary experiments show that this score led to a maximum increase of 26.8% (FDR 0.1%) and 21.6% (FDR 1%) for the DDA and the DIA identification, respectively.

Significance StatementA better prediction of fragmentation for peptides in mass spectrometry (MS) is beneficial to the peptide identification. As the MS/MS spectra record two-dimensional information of fragment ions derived from precursors, mass-to-charge ratio (m/z) and their corresponding intensities, besides the fragment intensity prediction, it is necessary to study the presence prediction. Although the presence prediction can be realized by enumerating all the possible fragmentation patterns of a peptide with equal probability or by selecting non-zero intensity fragment ions from the result of fragment intensity prediction, neither of these two methods is accurate enough. In this study, deep learning is leveraged to precisely predict the fragment ions of a given peptide. Based on the fragment presence prediction, fragment presence similarity between experimental spectra and predicted spectra can be calculated which is proved to promote the peptide detections both for DDA and for DIA data. A variable-gain stochastic pooling motif mediates information transfer from receptor assemblies into NF-κB A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IKK complex is an integration hub for cytokines that govern NF-{kappa}B signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here we track dynamics of IKK complexes and nuclear NF-{kappa}B to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveals their size, number, and timing relays cytokine-specific information with feedback control that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables parsimonious and cytokine-specific information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling.

One Sentence SummaryA variable-gain stochastic pooling motif mediates robust and tunable information transmission from the extracellular milieu into the cell. Effect of sublethal prenatal endotoxaemia on murine placental transport systems and lipid homeostasis Infection alters the expression of transporters that mediate the placental exchange of xenobiotics, lipids and cytokines. We hypothesized that lipopolysaccharide (LPS) modifies the expression of placental transport systems and lipid homeostasis. LPS (150 g/kg; i.p.) treatments were administered for 4 h or 24 h, animals were euthanized at gestational days (GD) 15.5 or 18.5, and maternal blood, foetuses and placentae were collected. Increased rates of foetal demise were observed at GD15.5 following LPS treatment, whereas at GD18.5, high rates of early labour occurred and were associated with distinct proinflammatory responses. LPS did not alter ABC transporter mRNA expression but decreased Fabppm at GD15.5 (LPS-4 h) and increased Fat/Cd36 lipid transporter mRNA at GD18.5 (LPS-4 h). At the protein level, breast cancer-related protein (BCRP) and Abcg1 levels were decreased in the placental labyrinth zone (Lz) at GD15.5, whereas P-glycoprotein (P-gp) and Bcrp Lz-immunostaining was decreased at GD18.5. In the placental junctional zone (Jz), P-gp, Bcrp and Abcg1 levels were higher at GD18.5. Specific maternal plasma and placental changes in triacylglycerol, free fatty acid, cholesterol, cholesterol ester and monoacylglycerol levels were detected in a gestational age-dependent manner. In conclusion, LPS-induced foetal death and early labour were associated with altered placental ABC and lipid transporter expression and deranged maternal plasma and placental lipid homeostasis. These changes likely modify foetal xenobiotic exposure and placental lipid exchange in cases of bacterial infection. Quantitative analysis of gene expression on the inactive human X chromosome The human X chromosome exists in active (Xa) and inactive (Xi) states. To quantify Xi gene expression and explore its implications, we conducted RNA sequencing in two cell types from individuals with one Xa and zero to three Xis. Linear models fit the data well, indicating equal contributions from each Xi and quantifying significant Xi-driven expression changes for 124 of 406 expressed X-chromosome genes. As revealed by allele-specific expression analyses, these Xi-driven changes reflect both i) Xi transcription and ii) Xi modulation - both positive and negative - of Xa transcript levels. Incorporating population and evolutionary measures of constraint on expression levels, we identified 13 X-chromosome genes most likely to drive the phenotypic consequences of natural variation in Xi copy number. These analytics and the underlying datasets offer a foundation for understanding Turner, Klinefelter, and other sex chromosome aneuploidy syndromes, and sex-chromosome effects on health and disease in euploid males and females. An isogenic collection of pluripotent stem cell lines with elevated α-synuclein expression -Synuclein (Syn) is a small, disordered protein that becomes aggregated in Lewy body diseases, such as Parkinsons disease (PD) and dementia with Lewy bodies (DLB). Human induced pluripotent stem cells (hiPSCs) potentially provide a tractable disease model to monitor early molecular changes associated with PD/DLB. We and others have previously derived hiPSC lines from patients with duplication and triplication of the SNCA gene, encoding for Syn. It is now recognised that to perform meaningful disease modelling with these hiPSC lines, it is critical to generate isogenic control cell lines that lack the disease causing mutations. In order to complement the existing and emerging hiPSC models for PD/DLB, we have generated an allelic series of Syn over-expressing hESC lines on the same isogenic background. An unresolved question is whether pluripotent stem cell lines, with elevated levels of Syn, can undergo efficient differentiation into dopaminergic and cortical neurons to model PD and DLB, respectively. We took advantage of our isogenic collection of hESC lines to determine if increased expression of Syn affects neural induction and neuronal differentiation. Clonal hESC lines with significantly different levels of Syn expression proliferated normally and maintained expression of pluripotent markers, such as OCT4. All cell lines efficiently produced PAX6+ neuroectoderm and there was no correlation between Syn expression and neural induction efficiency. Finally, global transcriptomic analysis of cortical differentiation of hESC lines with low or high levels of Syn expression demonstrated robust and similar induction of cortical neuronal expression profiles. Gene expression differences observed were unrelated to neural induction and neuronal differentiation. We conclude that elevated expression of Syn in human pluripotent stem cells does not adversely affect their neuronal differentiation potential and that collections of isogenic cell lines with differing levels of Syn expression are valid and suitable models to investigate synucleinopathies. Molecular Dynamics Simulations of Phytopthora sojae Avirulence Factor 5, PsAvh5, Define Membrane Binding, Inositolphosphate-3'-phosphate Interactions and Protein Mechanics Phytopthora Avirulence proteins are a primary target for development of rational chemical and biological control of some of the most devastating plant pathogens. Despite the sequencing of entire genomes, and characterization of many of these proteins at the chemical level, many questions remain regarding actual chemical and biological interactions involved. In addition, disputed roles of ligands, such as Inositolphosphate-3-phosphate and amino acids of important function remain unclear. To address some of these issues, we developed molecular models from structural elements and published data for Phytopthora sojae avirulence protein 5. Molecular dynamics simulations are used to study protein function, interactions involved primarily with lipids and membranes, and inositol derivatives. Our findings indicate that the protein is stable as a monomer, and in a dimeric form. Also, that these proteins interact with Inositolphosphate-3phosphate as a necessary membrane element, in binding. We identified several amino acids of importance, additional to defining the mechanical features of the protein within the binding process to different membranes. A high affinity, comparable to other membrane surface binding molecules of -219.54 Kcal for the dimer, and -176.61 for the monomer were determined. With either form, we found the inositolphosphate-3-phosphate to be essential in the membrane binding process. Our findings answer some of the debated questions while creating a point to further test avirulence proteins in general for functional aspects. Additionally, the structures and data can be utilized to provide a better starting point for rational design approaches to control this pathogen.